http://psychmethods.wiki.uib.no/api.php?action=feedcontributions&feedformat=atom&user=Sje025 2026-04-10T02:24:58Z User contributions MediaWiki 1.44.2 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=344 2024-09-03T13:45:52Z

<p>Sje025: /* Learning and exploring statistics */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed a [http://statstar.io/ helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> Statistical analyses are based upon a number of concepts and underlying assumptions. The [[Media:CrashCourseRefresher_Concepts.pdf|following lecture]] aims to give an introduction into such general statistical concepts, discussing, e.g., population and sample, levels of measurement, how to organize and first explore your data (using descriptive statistics), and prerequisites for conducting inference statistics such as a description of what research vs. statistical hypotheses are, several conceptualizations of the p-value and a discussion of statistical significance vs. effect size.<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses. Those are covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|first part of the following lecture]].&lt;br&gt;<br /> <br /> All analyses described above are used to explore manifest variables, i.e. variables that we can directly observe (and analyse). However, there are also [https://en.wikipedia.org/wiki/Latent_and_observable_variables latent variables] that are inferred indirectly through a mathematical model from observable variables. A typical example for such latent variables are personality dimensions, where we measure characteristics of that personality dimension with several items and afterwards combine them (e.g., by summing them up). A method to find or extract such dimensions based upon the pattern of correlations among questionnaire items is called (exploratory) factor analysis. The [[Media:FactorAnalysis_jamovi_Lecture.pdf|following lecture]] first describes the principles and inner workings of factor analysis (FA) before turning to how different factor-analytical methods (exploratory FA, principal component analysis, confirmatory FA and reliability analysis) are carried out in jamovi.&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/no/latest/ Norwegian], and [https://jamovi.readthedocs.io/de/latest/ German].&lt;br&gt;<br /> <br /> It is not only that jamovi implements its analyses as R-code under the hood, it also offers plenty of opportunity to combine the “safer” option of assembling analyses using a graphical user interface (for standard analyses) with the much broader range of analyses available in R. The [[Media:JamoviToR.pdf| following lecture]] first gives a brief introduction into R (what is it about, variable types, etc.) before demonstrating how to use R from within jamovi (using the [https://jamovi.readthedocs.io/en/latest/usermanual/um_6_jamovi_and_R.html#rj-editor Rj editor]) and how to use jamovi within R (jamovi can output the syntax for the analyses conducted and all analyses are available as [https://cran.r-project.org/package=jmv jmv] R-package, and the R-packages [https://cran.r-project.org/package=jmvconnect jmvconnect] and [https://cran.r-project.org/package=jmvReadWrite jmvReadWrite] help with handling datasets opened in jamovi and jamovi-files). The lecture ends with presenting two typical use cases: using analysis results (e.g., regression coefficients) and importing text data.<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=APA6_7_Changes&diff=343 2024-09-03T13:43:14Z

<p>Sje025: </p> <hr /> <div>= Most notable changes between the 6th and the 7th edition of the APA Publication Manual =<br /> Generally, one major change from the 6th to the 7th edition is that the 7th edition is much more &quot;user friendly&quot; (at least I experience it that way). There is a [https://www.youtube.com/watch?v=jOVZp8m0PCM&amp;t=150 video] summarizing the major changes, another (a bit lengthy; the first 2:30 can be dropped) going into more depth.&lt;br&gt;<br /> For those who don't want to purchase the book, at lot of the [https://apastyle.apa.org/style-grammar-guidelines basics] is covered on the [https://apastyle.apa.org APA-style web page]. What is particularly noteworthy is the steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], for [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. Furthermore, there are some [https://apastyle.apa.org/instructional-aids/ instructional aids].&lt;br&gt;<br /> Finally, the part of that manual that deals with what should be included in a manuscript has be extended significantly. It now forms the [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).<br /> <br /> == Formatting ==<br /> I mentioned this before, but I regard the [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers '''sample papers'''] as well as the [https://apastyle.apa.org/instructional-aids/heading-template-professional-paper.pdf overview on the use of headings] very instructive and incredibly helpful. Generally, APA7 is aiming to increase flexibility (e.g., with font choices) and coherence (with the headings), and the changes include:<br /> * There is increased flexibility regarding fonts, font options now include Calibri 11, Arial 11, Lucida Sans Unicode 10, Times New Roman 12, and Georgia 11 (only Times New Roman 12 was permitted before).<br /> * The running head on the title page no longer includes the words “Running head:”, only the (shortened) paper title (left) and the page number (right). Student papers may drop it.<br /> * The format of the headings was changed (it is more consistent in APA 7, and there is an overview at the inner book cover):<br /> ** it uses Title Case Headings (words in the title always begin with a capital letter) for all levels of headings (APA 6: only 1 to 3)<br /> ** Level 1 is centered, Level 2 and 3 are Flushed left and Level 4 and 5 are Indented<br /> ** Level 1, 2, and 4 are Bold, Level 3 and 5 are bold and italic<br /> ** Level 1 to 3 finish with a line feed, the new paragraph afterwards is indented<br /> ** Level 4 and 5 end with a period. The text begins immediately afterwards<br /> <br /> == Language use ==<br /> The [https://apastyle.apa.org/style-grammar-guidelines/bias-free-language/general-principles general principles for bias-free language] remained quite similar between APA6 and APA7. However, the principles are laid out more detailed in the seventh edition. A noteworthy change is:<br /> * The singular “they” or “their” is endorsed as a gender-neutral pronoun. (“A researcher’s career depends on how often he or she is cited.” → “[…] how often they are cited.”)<br /> <br /> == Figures and Tables ==<br /> Sorry if this is a repetition, I mentioned this before, but I regard the '''sample''' [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures '''figures'''] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables '''tables'''] incredibly helpful. Furthermore, there are two pages explaining the '''general rules''' for [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/tables '''tables'''] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/figures '''figures''']. Changes with the 7th edition are:<br /> * The formatting of figures and tables is now unified:<br /> ** Captions are now always above (APA 6 had them above for tables and below for figures).<br /> ** Notes are introduced for figures (with rules similar to tables: general notes first, specific notes afterwards).<br /> * The placement of tables becomes more flexible: they now can be placed within the text or after the reference list with 1 table / figure per page (APA 6 demanded the latter)<br /> <br /> == References ==<br /> The starting page for [https://apastyle.apa.org/style-grammar-guidelines/references/ references] on the [https://apastyle.apa.org APA style web page] contains a lot of useful things including the [https://apastyle.apa.org/style-grammar-guidelines/references/basic-principles basic principles] and the [https://apastyle.apa.org/style-grammar-guidelines/references/elements-list-entry elements] of reference list entries. Further, there is a wealth of [https://apastyle.apa.org/style-grammar-guidelines/references/examples '''reference examples''']!&lt;br&gt;<br /> Changes from the 6th to the 7th edition when it comes to references include:<br /> * the et al.-rule has changed – now you use et al. for three or more authors (the 3-to-6-author-rule for the first occurrence was dropped)<br /> * in the reference list:<br /> # The publisher location is no longer included (New York, NY: Simon &amp; Schuster → Simon &amp; Schuster).<br /> # Including the issue number became mandatory.<br /> # The DOI must now have to format: &lt;nowiki&gt;https://doi.org/ + DOI&lt;/nowiki&gt; (earlier it could be DOI: + DOI).<br /> # If the DOI is very long you can use a shortDOI (http://shortdoi.org/) by pasting the original DOI in the input field, the output can be used like: &lt;nowiki&gt;https://doi.org/f8vbpr&lt;/nowiki&gt;; for URLs preferably use the URL shortener of the web page owner (e.g., &lt;nowiki&gt;https://goo.gl/l6MS&lt;/nowiki&gt;), otherwise common providers such as bitly.com, tinyurl.com<br /> # Surnames and initials for up to 20 authors (instead of 7) should be provided.<br /> # URLs are no longer preceded by “Retrieved from,” unless a retrieval date is needed.<br /> # Articles that are only available electronically (e.g., in PLoS or Frontiers), i.e., which have an '''article number''' instead of pages '''must''' now '''be preceded by &quot;Article&quot;''', e.g., Koelsch, S., Enge, J., &amp; Jentschke, S. (2012). Cardiac signatures of personality. ''PloS One, 7''(2), &lt;span style=&quot;color: red;&quot;&gt;Article e31441&lt;/span&gt;. &lt;nowiki&gt;https://doi.org/10.1371/journal.pone.0031441&lt;/nowiki&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=342 2023-02-07T11:18:24Z

<p>Sje025: /* Quantitative data analyses */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> Statistical analyses are based upon a number of concepts and underlying assumptions. The [[Media:CrashCourseRefresher_Concepts.pdf|following lecture]] aims to give an introduction into such general statistical concepts, discussing, e.g., population and sample, levels of measurement, how to organize and first explore your data (using descriptive statistics), and prerequisites for conducting inference statistics such as a description of what research vs. statistical hypotheses are, several conceptualizations of the p-value and a discussion of statistical significance vs. effect size.<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses. Those are covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|first part of the following lecture]].&lt;br&gt;<br /> <br /> All analyses described above are used to explore manifest variables, i.e. variables that we can directly observe (and analyse). However, there are also [https://en.wikipedia.org/wiki/Latent_and_observable_variables latent variables] that are inferred indirectly through a mathematical model from observable variables. A typical example for such latent variables are personality dimensions, where we measure characteristics of that personality dimension with several items and afterwards combine them (e.g., by summing them up). A method to find or extract such dimensions based upon the pattern of correlations among questionnaire items is called (exploratory) factor analysis. The [[Media:FactorAnalysis_jamovi_Lecture.pdf|following lecture]] first describes the principles and inner workings of factor analysis (FA) before turning to how different factor-analytical methods (exploratory FA, principal component analysis, confirmatory FA and reliability analysis) are carried out in jamovi.&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/no/latest/ Norwegian], and [https://jamovi.readthedocs.io/de/latest/ German].&lt;br&gt;<br /> <br /> It is not only that jamovi implements its analyses as R-code under the hood, it also offers plenty of opportunity to combine the “safer” option of assembling analyses using a graphical user interface (for standard analyses) with the much broader range of analyses available in R. The [[Media:JamoviToR.pdf| following lecture]] first gives a brief introduction into R (what is it about, variable types, etc.) before demonstrating how to use R from within jamovi (using the [https://jamovi.readthedocs.io/en/latest/usermanual/um_6_jamovi_and_R.html#rj-editor Rj editor]) and how to use jamovi within R (jamovi can output the syntax for the analyses conducted and all analyses are available as [https://cran.r-project.org/package=jmv jmv] R-package, and the R-packages [https://cran.r-project.org/package=jmvconnect jmvconnect] and [https://cran.r-project.org/package=jmvReadWrite jmvReadWrite] help with handling datasets opened in jamovi and jamovi-files). The lecture ends with presenting two typical use cases: using analysis results (e.g., regression coefficients) and importing text data.<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=341 2023-02-07T11:17:16Z

<p>Sje025: /* Quantitative data analyses */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> Statistical analyses are based upon a number of concepts and underlying assumptions. The [[Media:CrashCourseRefresher_Concepts.pdf|following lecture]] aims to give an introduction into such general statistical concepts, discussing, e.g., population and sample, levels of measurement, how to organize and first explore your data (using descriptive statistics), and prerequisites for conducting inference statistics such as a description of what research vs. statistical hypotheses are, several conceptualizations of the p-value and a discussion of statistical significance vs. effect size.<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses. Those are covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|first part of the following lecture]].&lt;br&gt;<br /> <br /> All analyses described above are used to explore manifest variables, i.e. variables that we can directly observe (and analyse). However, there are also [https://en.wikipedia.org/wiki/Latent_and_observable_variables latent variables] that are inferred indirectly through a mathematical model from observable variables. A typical example for such latent variables are personality dimensions, where we measure characteristics of that personality dimension with several items and afterwards combine them (e.g., by summing them up). A method to find or extract such dimensions based upon the pattern of correlations among questionnaire items is called (exploratory) factor analysis. The [[Media:FactorAnalysis_jamovi_Lecture.pdf|following lecture]] first describes the principles and inner workings of factor analysis (FA) before turning to how different factor-analytical methods (exploratory FA, principal component analysis, confirmatory FA and reliability analysis) are carried out in jamovi.&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/no/latest/ Norwegian], and [https://jamovi.readthedocs.io/de/latest/ German].&lt;br&gt;<br /> <br /> It is not only that jamovi implements its analyses as R-code under the hood, it also offers plenty of opportunity to combine the “safer” option of assembling analyses using a graphical user interface (for standard analyses) with the much broader range of analyses available in R. The [[Media:JamoviToR.pdf| following lecture]] first gives a brief introduction into R (what is it about, variable types, etc.) before demonstrating how to use R from within jamovi (using the [Rj editor]) and how to use jamovi within R (jamovi can output the syntax for the analyses conducted and all analyses are available as [https://cran.r-project.org/package=jmv jmv] R-package, and the R-packages [https://cran.r-project.org/package=jmvconnect jmvconnect] and [https://cran.r-project.org/package=jmvReadWrite jmvReadWrite] help with handling datasets opened in jamovi and jamovi-files). The lecture ends with presenting two typical use cases: using analysis results (e.g., regression coefficients) and importing text data.<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Correlation_and_regression_analysis&diff=340 2023-02-07T11:16:00Z

<p>Sje025: </p> <hr /> <div>=Using jamovi=<br /> Correlation is covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|third part of an introductory lecture on uni- and bivariate statistics]]. Building upon that, [[Media:Regression_jamovi_Lecture.pdf|another lecture]] covers multivariate analyses. It begins with a basic introduction (what are typical research questions, what kind of variables are used, what assumptions and requirements need to be met to apply the method), continues with an overview over fundamental equations (incl. some do-it-yourself in Excel), introduces then major regression types (standard, sequential/hierarchical, statistical/stepwise) and ends with some important issues (limitations, aspects to be attentive of, etc.). The lecture also introduces how those analyses are carried out in [https://www.jamovi.org/ jamovi].<br /> <br /> For an introduction from another perspective, you can head to chapter 12 of [https://lsj.readthedocs.io/en/latest/Ch12/Ch12_Regression.html “learning statistics with jamovi”] or to a [https://www.youtube.com/watch?list=PLkk92zzyru5OAtc_ItUubaSSq6S_TGfRn&amp;v=gRhVjKNWiUs video introduction] by Barton Poulson from datalab.cc.<br /> <br /> =Using SPSS=<br /> The [[Media:Regression_SPSS_Lecture.pdf|lecture]] begins with a basic introduction (what are typical research questions, what kind of variables are used, what assumptions and requirements need to be met to apply the method), continues with an overview over fundamental equations (incl. some do-it-yourself in Excel), introduces then major regression types (standard, sequential/hierarchical, statistical/stepwise) and ends with some important issues (limitations, aspects to be attentive of, etc.).<br /> <br /> The [[Media:Regression_SPSS_Exercise.pdf|PC exercise]] deals with the practical aspects of carrying out regression analyses in SPSS. There are two major parts dealing with linear regression and logistic regression. The part on Linear regression analysis begins with an assignment (on how to check requirements for calculating a linear regression), then demonstrates the equivalency of correlation to Linear regression (if there is only one predictor), how multiple predictors can be included in the regression model (incl. different methods for adding predictors) and end with how to assess the quality of your model. This is followed by an assignment to test the acquired knowledge practically. The logistic (binary) regression part consists of a basic introduction on the method (focussing on how a logistic function can be used to convert from a continuous to a binary outcome), followed by an assignment to use the method practically.<br /> <br /> In addition, there is a file with an [[Media:Regression_SPSS_Assignment.pdf|additional assignment]].<br /> <br /> Finally, there are two ZIP-files: [[:File:DataFiles_Field_TabachnikFidell.zip|One]] with the data files required in the exercise and the assignments, [[Media:Regression_SPSS_SyntaxOutput.zip|another]] containing SPSS syntax (with comments) and SPSS output files for the analyses described in the main slides as well as for the additional assignments.<br /> <br /> =More in-depth on the theoretical background=<br /> Both lecture slides include practical examples for calculation: A [[Media:Regression_Step-by-step.ods|LibreOffice/Excel-file]] with a demonstration how a correlation (i.e., a very simple regression with one variable; example from Field (2018), Ch. 8) is calculated by hand.&lt;br&gt;<br /> In addition, there is a [[Media:Regression_Step-by-step.txt|syntax file]] to run a regression analysis in MATLAB / Octave (from Tabachnik &amp; Fidell, 2013, Ch. 5.4); the data can also be found in a [[Media:Regression_Step-by-step.zip|ZIP-file]] to replicate the analyses in SPSS), which is described in the [[Media:Regression_SPSS_Lecture.pdf|lecture slides]] when using SPSS.</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=PsychoPy&diff=339 2023-02-07T11:15:37Z

<p>Sje025: </p> <hr /> <div>The following two lectures provide a very basic introduction into [https://psychopy.org/ PsychoPy], an open-source cross-platform package allowing you to run a wide range of experiments in the behavioural sciences. The [[Media:PsychoPy1.pdf|first lecture]] provides an overview over PsychoPy and its graphical user interface, introduces several components that can be used to generate experiments (e.g., presenting text or sounds and obtaining feedback from the keyboard), how those can be combined into routines and ran several times using loops. It finally prepares you for the assignment to create a questionnaire yourself.&lt;br&gt;<br /> The [[Media:PsychoPy2.pdf|second lecture]] briefly introduces how to run experiments generated locally (on your own machine) as online experiments, how to evaluate data obtained from experiments in PsychoPy, and ends with discussing several considerations when preparing experiments such as randomization, types of stimuli (and how to prepare them), as well as tasks for the participants.<br /> <br /> On the PsychoPy web page, there is a wealth of further [https://workshops.psychopy.org/teaching/index.html resources for teaching and learning] to extend what is covered in the two lectures above.</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=PsychoPy&diff=338 2023-02-07T11:15:03Z

<p>Sje025: </p> <hr /> <div>The following two lectures provide a very basic introduction into [https://psychopy.org/ PsychoPy], an open-source cross-platform package allowing you to run a wide range of experiments in the behavioural sciences. The [[Media:PsychoPy1.pdf first lecture]] provides an overview over PsychoPy and its graphical user interface, introduces several components that can be used to generate experiments (e.g., presenting text or sounds and obtaining feedback from the keyboard), how those can be combined into routines and ran several times using loops. It finally prepares you for the assignment to create a questionnaire yourself.&lt;br&gt;<br /> The [[Media:PsychoPy2.pdf second lecture]] briefly introduces how to run experiments generated locally (on your own machine) as online experiments, how to evaluate data obtained from experiments in PsychoPy, and ends with discussing several considerations when preparing experiments such as randomization, types of stimuli (and how to prepare them), as well as tasks for the participants.<br /> <br /> On the PsychoPy web page, there is a wealth of further [https://workshops.psychopy.org/teaching/index.html resources for teaching and learning] to extend what is covered in the two lectures above.</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=337 2023-02-07T11:05:24Z

<p>Sje025: /* Quantitative data analyses */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> Statistical analyses are based upon a number of concepts and underlying assumptions. The [[Media:CrashCourseRefresher_Concepts.pdf|following lecture]] aims to give an introduction into such general statistical concepts, discussing, e.g., population and sample, levels of measurement, how to organize and first explore your data (using descriptive statistics), and prerequisites for conducting inference statistics such as a description of what research vs. statistical hypotheses are, several conceptualizations of the p-value and a discussion of statistical significance vs. effect size.<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses. Those are covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|first part of the following lecture]].&lt;br&gt;<br /> <br /> All analyses described above are used to explore manifest variables, i.e. variables that we can directly observe (and analyse). However, there are also [https://en.wikipedia.org/wiki/Latent_and_observable_variables latent variables] that are inferred indirectly through a mathematical model from observable variables. A typical example for such latent variables are personality dimensions, where we measure characteristics of that personality dimension with several items and afterwards combine them (e.g., by summing them up). A method to find or extract such dimensions based upon the pattern of correlations among questionnaire items is called (exploratory) factor analysis. The [[Media:FactorAnalysis_jamovi_Lecture.pdf|following lecture]] first describes the principles and inner workings of factor analysis (FA) before turning to how different factor-analytical methods (exploratory FA, principal component analysis, confirmatory FA and reliability analysis) are carried out in jamovi.&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> It is not only that jamovi implements its analyses as R-code under the hood, it also offers plenty of opportunity to combine the “safer” option of assembling analyses using a graphical user interface (for standard analyses) with the much broader range of analyses available in R. The [[Media:JamoviToR.pdf| following lecture]] first gives a brief introduction into R (what is it about, variable types, etc.) before demonstrating how to use R from within jamovi (using the [Rj editor]) and how to use jamovi within R (jamovi can output the syntax for the analyses conducted and all analyses are available as [https://cran.r-project.org/package=jmv jmv] R-package, and the R-packages [https://cran.r-project.org/package=jmvconnect jmvconnect] and [https://cran.r-project.org/package=jmvReadWrite jmvReadWrite] help with handling datasets opened in jamovi and jamovi-files). The lecture ends with presenting two typical use cases: using analysis results (e.g., regression coefficients) and importing text data.<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=T-test_and_Analysis_of_Variance_(ANOVA)&diff=336 2023-02-07T10:59:55Z

<p>Sje025: /* More in-depth on the theoretical background */</p> <hr /> <div>=Using jamovi=<br /> t-tests are covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|second part of an introductory lecture on uni- and bivariate statistics]]. Building upon that, [[Media:AnalysisOfVariance_jamovi_Lecture.pdf|another lecture]] covers multivariate analyses. It first introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). Then, the Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, it will be described how several kinds of the ANOVA can be carried out in jamovi, starting with a simple One-Way ANOVA, extending it into a factorial ANOVA, adding continuous covariates (ANCOVA) and ending with a repeated-measures ANOVA.<br /> <br /> For an introduction from another perspective, you can head to [https://lsj.readthedocs.io/en/latest/Ch13/Ch13_ANOVA.html chapter 13] and [https://lsj.readthedocs.io/en/latest/Ch14/Ch14_ANOVA2.html chapter 14] of “learning statistics with jamovi” or to a [https://www.youtube.com/watch?v=GcbMG6sizXs&amp;list=PLkk92zzyru5OAtc_ItUubaSSq6S_TGfRn&amp;index=30 video introduction] by Barton Poulson from datalab.cc.<br /> <br /> =Using SPSS=<br /> The [[Media:AnalysisOfVariance_SPSS_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).&lt;br&gt;<br /> The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.<br /> <br /> In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf|additional assignments]], and two further ZIP-files accompanying it: [[Media:DataFiles_Field_TabachnikFidell.zip|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.<br /> <br /> =More in-depth on the theoretical background=<br /> Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field, 2018; Ch. 12) is calculated by hand.&lt;br&gt;<br /> The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik &amp; Fidell, 2013; Ch. 6, 7, 8).</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=T-test_and_Analysis_of_Variance_(ANOVA)&diff=335 2023-02-07T10:59:33Z

<p>Sje025: /* More in-depth on the theoretical background */</p> <hr /> <div>=Using jamovi=<br /> t-tests are covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|second part of an introductory lecture on uni- and bivariate statistics]]. Building upon that, [[Media:AnalysisOfVariance_jamovi_Lecture.pdf|another lecture]] covers multivariate analyses. It first introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). Then, the Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, it will be described how several kinds of the ANOVA can be carried out in jamovi, starting with a simple One-Way ANOVA, extending it into a factorial ANOVA, adding continuous covariates (ANCOVA) and ending with a repeated-measures ANOVA.<br /> <br /> For an introduction from another perspective, you can head to [https://lsj.readthedocs.io/en/latest/Ch13/Ch13_ANOVA.html chapter 13] and [https://lsj.readthedocs.io/en/latest/Ch14/Ch14_ANOVA2.html chapter 14] of “learning statistics with jamovi” or to a [https://www.youtube.com/watch?v=GcbMG6sizXs&amp;list=PLkk92zzyru5OAtc_ItUubaSSq6S_TGfRn&amp;index=30 video introduction] by Barton Poulson from datalab.cc.<br /> <br /> =Using SPSS=<br /> The [[Media:AnalysisOfVariance_SPSS_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).&lt;br&gt;<br /> The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.<br /> <br /> In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf|additional assignments]], and two further ZIP-files accompanying it: [[Media:DataFiles_Field_TabachnikFidell.zip|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.<br /> <br /> =More in-depth on the theoretical background=<br /> Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.&lt;br&gt;<br /> The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik &amp; Fidell, 2013; Ch. 6, 7, 8).</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=T-test_and_Analysis_of_Variance_(ANOVA)&diff=334 2023-02-07T10:58:05Z

<p>Sje025: </p> <hr /> <div>=Using jamovi=<br /> t-tests are covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|second part of an introductory lecture on uni- and bivariate statistics]]. Building upon that, [[Media:AnalysisOfVariance_jamovi_Lecture.pdf|another lecture]] covers multivariate analyses. It first introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). Then, the Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, it will be described how several kinds of the ANOVA can be carried out in jamovi, starting with a simple One-Way ANOVA, extending it into a factorial ANOVA, adding continuous covariates (ANCOVA) and ending with a repeated-measures ANOVA.<br /> <br /> For an introduction from another perspective, you can head to [https://lsj.readthedocs.io/en/latest/Ch13/Ch13_ANOVA.html chapter 13] and [https://lsj.readthedocs.io/en/latest/Ch14/Ch14_ANOVA2.html chapter 14] of “learning statistics with jamovi” or to a [https://www.youtube.com/watch?v=GcbMG6sizXs&amp;list=PLkk92zzyru5OAtc_ItUubaSSq6S_TGfRn&amp;index=30 video introduction] by Barton Poulson from datalab.cc.<br /> <br /> =Using SPSS=<br /> The [[Media:AnalysisOfVariance_SPSS_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).&lt;br&gt;<br /> The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.<br /> <br /> In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf|additional assignments]], and two further ZIP-files accompanying it: [[Media:DataFiles_Field_TabachnikFidell.zip|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.<br /> <br /> =More in-depth on the theoretical background=<br /> Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.&lt;br&gt;<br /> The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik &amp; Fidell (2013), Ch. 6, 7, 8).</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Correlation_and_regression_analysis&diff=333 2023-02-07T10:53:34Z

<p>Sje025: </p> <hr /> <div>=Using jamovi=<br /> Correlation is covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|third part of an introductory lecture on uni- and bivariate statistics]]. Building upon that, [[Media:Regression_jamovi_Lecture.pdf|another lecture ]] covers multivariate analyses. It begins with a basic introduction (what are typical research questions, what kind of variables are used, what assumptions and requirements need to be met to apply the method), continues with an overview over fundamental equations (incl. some do-it-yourself in Excel), introduces then major regression types (standard, sequential/hierarchical, statistical/stepwise) and ends with some important issues (limitations, aspects to be attentive of, etc.). The lecture also introduces how those analyses are carried out in [https://www.jamovi.org/ jamovi].<br /> <br /> For an introduction from another perspective, you can head to chapter 12 of [https://lsj.readthedocs.io/en/latest/Ch12/Ch12_Regression.html “learning statistics with jamovi”] or to a [https://www.youtube.com/watch?list=PLkk92zzyru5OAtc_ItUubaSSq6S_TGfRn&amp;v=gRhVjKNWiUs video introduction] by Barton Poulson from datalab.cc.<br /> <br /> =Using SPSS=<br /> The [[Media:Regression_SPSS_Lecture.pdf|lecture]] begins with a basic introduction (what are typical research questions, what kind of variables are used, what assumptions and requirements need to be met to apply the method), continues with an overview over fundamental equations (incl. some do-it-yourself in Excel), introduces then major regression types (standard, sequential/hierarchical, statistical/stepwise) and ends with some important issues (limitations, aspects to be attentive of, etc.).<br /> <br /> The [[Media:Regression_SPSS_Exercise.pdf|PC exercise]] deals with the practical aspects of carrying out regression analyses in SPSS. There are two major parts dealing with linear regression and logistic regression. The part on Linear regression analysis begins with an assignment (on how to check requirements for calculating a linear regression), then demonstrates the equivalency of correlation to Linear regression (if there is only one predictor), how multiple predictors can be included in the regression model (incl. different methods for adding predictors) and end with how to assess the quality of your model. This is followed by an assignment to test the acquired knowledge practically. The logistic (binary) regression part consists of a basic introduction on the method (focussing on how a logistic function can be used to convert from a continuous to a binary outcome), followed by an assignment to use the method practically.<br /> <br /> In addition, there is a file with an [[Media:Regression_SPSS_Assignment.pdf|additional assignment]].<br /> <br /> Finally, there are two ZIP-files: [[:File:DataFiles_Field_TabachnikFidell.zip|One]] with the data files required in the exercise and the assignments, [[Media:Regression_SPSS_SyntaxOutput.zip|another]] containing SPSS syntax (with comments) and SPSS output files for the analyses described in the main slides as well as for the additional assignments.<br /> <br /> =More in-depth on the theoretical background=<br /> Both lecture slides include practical examples for calculation: A [[Media:Regression_Step-by-step.ods|LibreOffice/Excel-file]] with a demonstration how a correlation (i.e., a very simple regression with one variable; example from Field (2018), Ch. 8) is calculated by hand.&lt;br&gt;<br /> In addition, there is a [[Media:Regression_Step-by-step.txt|syntax file]] to run a regression analysis in MATLAB / Octave (from Tabachnik &amp; Fidell, 2013, Ch. 5.4); the data can also be found in a [[Media:Regression_Step-by-step.zip|ZIP-file]] to replicate the analyses in SPSS), which is described in the [[Media:Regression_SPSS_Lecture.pdf|lecture slides]] when using SPSS.</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Correlation_and_regression_analysis&diff=332 2023-02-07T10:52:25Z

<p>Sje025: /* Using jamovi */</p> <hr /> <div>=Using jamovi=<br /> Correlation is covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|third part of an introductory lecture on uni- and bivariate statistics]]. [[Media:Regression_jamovi_Lecture.pdf|Another lecture ]] builds upon that by covering multivariate analyses. It begins with a basic introduction (what are typical research questions, what kind of variables are used, what assumptions and requirements need to be met to apply the method), continues with an overview over fundamental equations (incl. some do-it-yourself in Excel), introduces then major regression types (standard, sequential/hierarchical, statistical/stepwise) and ends with some important issues (limitations, aspects to be attentive of, etc.). The lecture also introduces how those analyses are carried out in [https://www.jamovi.org/ jamovi].<br /> <br /> For an introduction from another perspective, you can head to chapter 12 of [https://lsj.readthedocs.io/en/latest/Ch12/Ch12_Regression.html “learning statistics with jamovi”] or to a [https://www.youtube.com/watch?list=PLkk92zzyru5OAtc_ItUubaSSq6S_TGfRn&amp;v=gRhVjKNWiUs video introduction] by Barton Poulson from datalab.cc.<br /> <br /> =Using SPSS=<br /> The [[Media:Regression_SPSS_Lecture.pdf|lecture]] begins with a basic introduction (what are typical research questions, what kind of variables are used, what assumptions and requirements need to be met to apply the method), continues with an overview over fundamental equations (incl. some do-it-yourself in Excel), introduces then major regression types (standard, sequential/hierarchical, statistical/stepwise) and ends with some important issues (limitations, aspects to be attentive of, etc.).<br /> <br /> The [[Media:Regression_SPSS_Exercise.pdf|PC exercise]] deals with the practical aspects of carrying out regression analyses in SPSS. There are two major parts dealing with linear regression and logistic regression. The part on Linear regression analysis begins with an assignment (on how to check requirements for calculating a linear regression), then demonstrates the equivalency of correlation to Linear regression (if there is only one predictor), how multiple predictors can be included in the regression model (incl. different methods for adding predictors) and end with how to assess the quality of your model. This is followed by an assignment to test the acquired knowledge practically. The logistic (binary) regression part consists of a basic introduction on the method (focussing on how a logistic function can be used to convert from a continuous to a binary outcome), followed by an assignment to use the method practically.<br /> <br /> In addition, there is a file with an [[Media:Regression_SPSS_Assignment.pdf|additional assignment]].<br /> <br /> Finally, there are two ZIP-files: [[:File:DataFiles_Field_TabachnikFidell.zip|One]] with the data files required in the exercise and the assignments, [[Media:Regression_SPSS_SyntaxOutput.zip|another]] containing SPSS syntax (with comments) and SPSS output files for the analyses described in the main slides as well as for the additional assignments.<br /> <br /> =More in-depth on the theoretical background=<br /> Both lecture slides include practical examples for calculation: A [[Media:Regression_Step-by-step.ods|LibreOffice/Excel-file]] with a demonstration how a correlation (i.e., a very simple regression with one variable; example from Field (2018), Ch. 8) is calculated by hand.&lt;br&gt;<br /> In addition, there is a [[Media:Regression_Step-by-step.txt|syntax file]] to run a regression analysis in MATLAB / Octave (from Tabachnik &amp; Fidell, 2013, Ch. 5.4); the data can also be found in a [[Media:Regression_Step-by-step.zip|ZIP-file]] to replicate the analyses in SPSS), which is described in the [[Media:Regression_SPSS_Lecture.pdf|lecture slides]] when using SPSS.</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=331 2023-02-07T10:51:38Z

<p>Sje025: /* Quantitative data analyses */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[Media:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses. Those are covered as the [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|first part of the following lecture]].&lt;br&gt;<br /> <br /> All analyses described above are used to explore manifest variables, i.e. variables that we can directly observe (and analyse). However, there are also [https://en.wikipedia.org/wiki/Latent_and_observable_variables latent variables] that are inferred indirectly through a mathematical model from observable variables. A typical example for such latent variables are personality dimensions, where we measure characteristics of that personality dimension with several items and afterwards combine them (e.g., by summing them up). A method to find or extract such dimensions based upon the pattern of correlations among questionnaire items is called (exploratory) factor analysis. The [[Media:FactorAnalysis_jamovi_Lecture.pdf|following lecture]] first describes the principles and inner workings of factor analysis (FA) before turning to how different factor-analytical methods (exploratory FA, principal component analysis, confirmatory FA and reliability analysis) are carried out in jamovi.&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> It is not only that jamovi implements its analyses as R-code under the hood, it also offers plenty of opportunity to combine the “safer” option of assembling analyses using a graphical user interface (for standard analyses) with the much broader range of analyses available in R. The [[Media:JamoviToR.pdf| following lecture]] first gives a brief introduction into R (what is it about, variable types, etc.) before demonstrating how to use R from within jamovi (using the [Rj editor]) and how to use jamovi within R (jamovi can output the syntax for the analyses conducted and all analyses are available as [https://cran.r-project.org/package=jmv jmv] R-package, and the R-packages [https://cran.r-project.org/package=jmvconnect jmvconnect] and [https://cran.r-project.org/package=jmvReadWrite jmvReadWrite] help with handling datasets opened in jamovi and jamovi-files). The lecture ends with presenting two typical use cases: using analysis results (e.g., regression coefficients) and importing text data.<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=330 2023-02-07T10:48:01Z

<p>Sje025: /* Evaluation methods */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[Media:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses. Those are covered as the first part of [[Media:CrashCourseRefresher_jamovi_Analyses.pdf|the following lecture]].&lt;br&gt;<br /> <br /> All analyses described above are used to explore manifest variables, i.e. variables that we can directly observe (and analyse). However, there are also [https://en.wikipedia.org/wiki/Latent_and_observable_variables latent variables] that are inferred indirectly through a mathematical model from observable variables. A typical example for such latent variables are personality dimensions, where we measure characteristics of that personality dimension with several items and afterwards combine them (e.g., by summing them up). A method to find or extract such dimensions based upon the pattern of correlations among questionnaire items is called (exploratory) factor analysis. The [[Media:FactorAnalysis_jamovi_Lecture.pdf|following lecture]] first describes the principles and inner workings of factor analysis (FA) before turning to how different factor-analytical methods (exploratory FA, principal component analysis, confirmatory FA and reliability analysis) are carried out in jamovi.&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> It is not only that jamovi implements its analyses as R-code under the hood, it also offers plenty of opportunity to combine the “safer” option of assembling analyses using a graphical user interface (for standard analyses) with the much broader range of analyses available in R. The [[Media:JamoviToR.pdf| following lecture]] first gives a brief introduction into R (what is it about, variable types, etc.) before demonstrating how to use R from within jamovi (using the [Rj editor]) and how to use jamovi within R (jamovi can output the syntax for the analyses conducted and all analyses are available as [https://cran.r-project.org/package=jmv jmv] R-package, and the R-packages [https://cran.r-project.org/package=jmvconnect jmvconnect] and [https://cran.r-project.org/package=jmvReadWrite jmvReadWrite] help with handling datasets opened in jamovi and jamovi-files). The lecture ends with presenting two typical use cases: using analysis results (e.g., regression coefficients) and importing text data.<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=APA6_7_Changes&diff=329 2023-02-07T10:22:28Z

<p>Sje025: /* Figures and Tables */</p> <hr /> <div>= Most notable changes between the 6th and the 7th edition of the APA Publication Manual =<br /> Generally, one major change from the 6th to the 7th edition is that the 7th edition is much more &quot;user friendly&quot; (at least I experience it that way). There is a [https://www.youtube.com/watch?v=jOVZp8m0PCM video] summarizing the major changes, another (a bit lengthy; the first 2:30 can be dropped) [https://www.youtube.com/watch?v=jOVZp8m0PCM&amp;t=150 video] going into more depth.&lt;br&gt;<br /> For those who don't want to purchase the book, at lot of the [https://apastyle.apa.org/style-grammar-guidelines basics] is covered on the [https://apastyle.apa.org APA-style web page]. What is particularly noteworthy is the steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], for [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. Furthermore, there are some [https://apastyle.apa.org/instructional-aids/ instructional aids].&lt;br&gt;<br /> Finally, the part of that manual that deals with what should be included in a manuscript has be extended significantly. It now forms the [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).<br /> <br /> == Formatting ==<br /> I mentioned this before, but I regard the [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers '''sample papers'''] as well as the [https://apastyle.apa.org/instructional-aids/heading-template-professional-paper.pdf overview on the use of headings] very instructive and incredibly helpful. Generally, APA7 is aiming to increase flexibility (e.g., with font choices) and coherence (with the headings), and the changes include:<br /> * There is increased flexibility regarding fonts, font options now include Calibri 11, Arial 11, Lucida Sans Unicode 10, Times New Roman 12, and Georgia 11 (only Times New Roman 12 was permitted before).<br /> * The running head on the title page no longer includes the words “Running head:”, only the (shortened) paper title (left) and the page number (right). Student papers may drop it.<br /> * The format of the headings was changed (it is more consistent in APA 7, and there is an overview at the inner book cover):<br /> ** it uses Title Case Headings (words in the title always begin with a capital letter) for all levels of headings (APA 6: only 1 to 3)<br /> ** Level 1 is centered, Level 2 and 3 are Flushed left and Level 4 and 5 are Indented<br /> ** Level 1, 2, and 4 are Bold, Level 3 and 5 are bold and italic<br /> ** Level 1 to 3 finish with a line feed, the new paragraph afterwards is indented<br /> ** Level 4 and 5 end with a period. The text begins immediately afterwards<br /> <br /> == Language use ==<br /> The [https://apastyle.apa.org/style-grammar-guidelines/bias-free-language/general-principles general principles for bias-free language] remained quite similar between APA6 and APA7. However, the principles are laid out more detailed in the seventh edition. A noteworthy change is:<br /> * The singular “they” or “their” is endorsed as a gender-neutral pronoun. (“A researcher’s career depends on how often he or she is cited.” → “[…] how often they are cited.”)<br /> <br /> == Figures and Tables ==<br /> Sorry if this is a repetition, I mentioned this before, but I regard the '''sample''' [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures '''figures'''] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables '''tables'''] incredibly helpful. Furthermore, there are two pages explaining the '''general rules''' for [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/tables '''tables'''] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/figures '''figures''']. Changes with the 7th edition are:<br /> * The formatting of figures and tables is now unified:<br /> ** Captions are now always above (APA 6 had them above for tables and below for figures).<br /> ** Notes are introduced for figures (with rules similar to tables: general notes first, specific notes afterwards).<br /> * The placement of tables becomes more flexible: they now can be placed within the text or after the reference list with 1 table / figure per page (APA 6 demanded the latter)<br /> <br /> == References ==<br /> The starting page for [https://apastyle.apa.org/style-grammar-guidelines/references/ references] on the [https://apastyle.apa.org APA style web page] contains a lot of useful things including the [https://apastyle.apa.org/style-grammar-guidelines/references/basic-principles basic principles] and the [https://apastyle.apa.org/style-grammar-guidelines/references/elements-list-entry elements] of reference list entries. Further, there is a wealth of [https://apastyle.apa.org/style-grammar-guidelines/references/examples '''reference examples''']!&lt;br&gt;<br /> Changes from the 6th to the 7th edition when it comes to references include:<br /> * the et al.-rule has changed – now you use et al. for three or more authors (the 3-to-6-author-rule for the first occurrence was dropped)<br /> * in the reference list:<br /> # The publisher location is no longer included (New York, NY: Simon &amp; Schuster → Simon &amp; Schuster).<br /> # Including the issue number became mandatory.<br /> # The DOI must now have to format: &lt;nowiki&gt;https://doi.org/ + DOI&lt;/nowiki&gt; (earlier it could be DOI: + DOI).<br /> # If the DOI is very long you can use a shortDOI (http://shortdoi.org/) by pasting the original DOI in the input field, the output can be used like: &lt;nowiki&gt;https://doi.org/f8vbpr&lt;/nowiki&gt;; for URLs preferably use the URL shortener of the web page owner (e.g., &lt;nowiki&gt;https://goo.gl/l6MS&lt;/nowiki&gt;), otherwise common providers such as bitly.com, tinyurl.com<br /> # Surnames and initials for up to 20 authors (instead of 7) should be provided.<br /> # URLs are no longer preceded by “Retrieved from,” unless a retrieval date is needed.<br /> # Articles that are only available electronically (e.g., in PLoS or Frontiers), i.e., which have an '''article number''' instead of pages '''must''' now '''be preceded by &quot;Article&quot;''', e.g., Koelsch, S., Enge, J., &amp; Jentschke, S. (2012). Cardiac signatures of personality. ''PloS One, 7''(2), &lt;span style=&quot;color: red;&quot;&gt;Article e31441&lt;/span&gt;. &lt;nowiki&gt;https://doi.org/10.1371/journal.pone.0031441&lt;/nowiki&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=328 2023-02-07T10:21:07Z

<p>Sje025: /* Evaluation methods */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[Media:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> TBA: Uni- and bivariate analyses<br /> [[Media:CrashCourseRefresher_jamovi_Analyses.pdf]]<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses.<br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> TBA: Factor analysis<br /> [[Media:FactorAnalysis_jamovi_Lecture.pdf]]&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> TBA: jamovi and R<br /> [[Media:JamoviToR.pdf]]<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=327 2023-02-07T10:20:23Z

<p>Sje025: /* Evaluation methods */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[File:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> TBA: Uni- and bivariate analyses<br /> [[File:CrashCourseRefresher_jamovi_Analyses.pdf]]<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses.<br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> TBA: Factor analysis<br /> [[:File:FactorAnalysis_jamovi_Lecture.pdf]]&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> TBA: jamovi and R<br /> [[:File:JamoviToR.pdf]]<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=326 2023-02-07T10:20:10Z

<p>Sje025: /* Evaluation methods */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[File:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[File:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> TBA: Uni- and bivariate analyses<br /> [[File:CrashCourseRefresher_jamovi_Analyses.pdf]]<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses.<br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> TBA: Factor analysis<br /> [[:File:FactorAnalysis_jamovi_Lecture.pdf]]&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> TBA: jamovi and R<br /> [[:File:JamoviToR.pdf]]<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=PsychoPy&diff=325 2023-02-07T10:17:35Z

<p>Sje025: </p> <hr /> <div>TBA&lt;br&gt;<br /> [[:File:PsychoPy1.pdf]]&lt;br&gt;<br /> [[:File:PsychoPy2.pdf]]&lt;br&gt;<br /> <br /> On the PsychoPy web page, there is a wealth of further [https://workshops.psychopy.org/teaching/index.html resources for teaching and learning] to extend what is covered in the two lectures above.</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=PsychoPy&diff=324 2023-02-06T18:18:22Z

<p>Sje025: </p> <hr /> <div>TBA&lt;br&gt;<br /> [[:File:PsychoPy1.pdf]]&lt;br&gt;<br /> [[:File:PsychoPy2.pdf]]&lt;br&gt;<br /> <br /> https://workshops.psychopy.org/teaching/index.html</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Reference_management&diff=323 2023-02-06T18:11:57Z

<p>Sje025: </p> <hr /> <div>=Zotero=<br /> Zotero is a reference management software for managing bibliographic data and research materials (such as PDFs). It is available for Windows, MacOS and Linux and it is [[open source]] (i.e., you can [https://www.zotero.org/download download it free of charge]), programmed at the Center for History and New Media at George Mason University. Features include a web interface to manage your references, browser integration (i.e., automatically adding an article PDF or a web page into your reference library), online synchronization (i.e., backing up your library of references), generation of formatted citations, footnotes, and bibliographies, as well as integration with Microsoft Word, LibreOffice Writer and Google Docs (i.e., you can easily create citations and a reference list in those word processors). In addition, it supports BibTeX (LaTeX). The programs allow collaboration and sharing of libraries (e.g., if you want to share literature within a student group).<br /> <br /> =Mendeley=<br /> Mendeley is a desktop and web application produced by Elsevier to manage and share research documents, discover research data, and collaborate online. It combines Mendeley Desktop, a PDF and reference management application available for Windows, MacOS and Linux. It also provides Mendeley for Android and iOS, and Mendeley Web, an online social network for researchers. The Software is not open source (but you can [https://www.mendeley.com download it free of charge]).<br /> <br /> =EndNote=<br /> EndNote is a commercial reference management software used to handle bibliographies and references when writing essays and articles. The program is available for Mac and PC but not for Linux. It is produced by Clarivate Analytics (formerly Thomson Reuters). EndNote is available free of charge to students and employees at UiB (for [https://www.uib.no/en/ub/79568/endnote-and-other-referencing-tools further instructions and guidance]). This is one advantage because library staff might be able to help you when you have questions. Another advantage is its integration with ISI Web of Knowledge (a comprehensive database for scientific literature). The disadvantage is that it is a commercial software (i.e. you have to pay for it if want to continue you to use it after your time at UiB, the price is about [https://www.endnote.no 2 500 kr]).</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=LaTeX&diff=322 2023-02-06T18:11:04Z

<p>Sje025: Created page with &quot;TBA&lt;br&gt;&quot;</p> <hr /> <div>TBA&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=PsychoPy&diff=321 2023-02-06T18:10:17Z

<p>Sje025: </p> <hr /> <div>TBA&lt;br&gt;<br /> [[:File:PsychoPy1.pdf]]&lt;br&gt;<br /> [[:File:PsychoPy2.pdf]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=PsychoPy&diff=320 2023-02-06T18:09:49Z

<p>Sje025: </p> <hr /> <div>TBA<br /> [[:File:PsychoPy1.pdf]]<br /> [[:File:PsychoPy2.pdf]]</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:PsychoPy2.pdf&diff=319 2023-02-06T18:09:37Z

<p>Sje025: File uploaded with MsUpload</p> <hr /> <div>File uploaded with MsUpload</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:PsychoPy1.pdf&diff=318 2023-02-06T18:09:37Z

<p>Sje025: File uploaded with MsUpload</p> <hr /> <div>File uploaded with MsUpload</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=317 2023-02-06T18:09:23Z

<p>Sje025: /* Experiments */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[:File:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> TBA: Uni- and bivariate analyses<br /> [[:File:CrashCourseRefresher_jamovi_Analyses.pdf]]<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses.<br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> TBA: Factor analysis<br /> [[:File:FactorAnalysis_jamovi_Lecture.pdf]]&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> TBA: jamovi and R<br /> [[:File:JamoviToR.pdf]]<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:LiteratureSearch.pdf&diff=316 2023-02-06T18:08:49Z

<p>Sje025: Sje025 uploaded a new version of File:LiteratureSearch.pdf</p> <hr /> <div></div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=315 2023-02-06T18:08:05Z

<p>Sje025: /* Quantitative data analyses */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[Media:PsychoPy.pdf|PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[:File:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> TBA: Uni- and bivariate analyses<br /> [[:File:CrashCourseRefresher_jamovi_Analyses.pdf]]<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use frequency analyses.<br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> TBA: Factor analysis<br /> [[:File:FactorAnalysis_jamovi_Lecture.pdf]]&lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> TBA: jamovi and R<br /> [[:File:JamoviToR.pdf]]<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:JamoviToR.pdf&diff=314 2023-02-06T18:03:40Z

<p>Sje025: File uploaded with MsUpload</p> <hr /> <div>File uploaded with MsUpload</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:FactorAnalysis_jamovi_Lecture.pdf&diff=313 2023-02-06T18:03:39Z

<p>Sje025: File uploaded with MsUpload</p> <hr /> <div>File uploaded with MsUpload</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:ResearchEthics.pdf&diff=312 2023-02-06T18:01:39Z

<p>Sje025: File uploaded with MsUpload</p> <hr /> <div>File uploaded with MsUpload</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:ExperimentalDesign.pdf&diff=311 2023-02-06T18:00:45Z

<p>Sje025: Sje025 uploaded a new version of File:ExperimentalDesign.pdf</p> <hr /> <div>Lecture slides on experimental design</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=310 2023-02-06T17:59:14Z

<p>Sje025: /* Extracting data */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[Media:PsychoPy.pdf|PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Shell_Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[:File:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> TBA: Uni- and bivariate analyses<br /> [[:File:CrashCourseRefresher_jamovi_Analyses.pdf]]<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use [[Media:FrequencyAnalyses.pdf|Frequency analyses]].&lt;br&gt;<br /> &lt;br&gt;<br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> &lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=309 2023-02-06T17:58:23Z

<p>Sje025: /* Conducting your research in accordance with legal requirements */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[Media:PsychoPy.pdf|PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:ResearchEthics.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[:File:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> TBA: Uni- and bivariate analyses<br /> [[:File:CrashCourseRefresher_jamovi_Analyses.pdf]]<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use [[Media:FrequencyAnalyses.pdf|Frequency analyses]].&lt;br&gt;<br /> &lt;br&gt;<br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> &lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=308 2023-02-06T17:57:09Z

<p>Sje025: /* Presenting your results */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[Media:PsychoPy.pdf|PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:Ethics_and_data_protection.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[:File:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> TBA: Uni- and bivariate analyses<br /> [[:File:CrashCourseRefresher_jamovi_Analyses.pdf]]<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use [[Media:FrequencyAnalyses.pdf|Frequency analyses]].&lt;br&gt;<br /> &lt;br&gt;<br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> &lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:PresentationTechnique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics, as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:PresentationTechnique.pdf&diff=307 2023-02-06T17:57:05Z

<p>Sje025: File uploaded with MsUpload</p> <hr /> <div>File uploaded with MsUpload</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=Psychological_Methods:_Wiki&diff=306 2023-02-06T17:55:33Z

<p>Sje025: /* Quantitative data analyses */</p> <hr /> <div>=Planning your study=<br /> <br /> ==Literature search==<br /> The following [[Media:LiteratureSearch.pdf|lecture]] gives an overview: (1) on the differences between search engines (e.g., Google Scholar) vs. databases (e.g., PsychINFO, PubMed); (2) on the choice of search terms: their selection, combination (boolean), and further operators (e.g., wildcards) to help with the search; (3) a comparison of systematic reviews vs. meta-analyses (with a focus on aims and procedure; (4) on the use of Google Scholar, Oria, Web of Science, and PubMed (incl. some practical hints); and (5) on different reference management software packages: Zotero, Mendeley, and EndNote (see [[Reference_management|here]] for a more detailed overview).&lt;br&gt;<br /> There is also a fantastic introduction on [https://training.cochrane.org/interactivelearning cochrane.org]. Cochrane is an organization that summarizes scientific evidence and publishes them as literature reviews / meta-analyses aiming to enhance healthcare knowledge and clinical decision making.&lt;br&gt;<br /> On the [http://www.prisma-statement.org PRISMA-web page] will you find a [http://www.prisma-statement.org/documents/PRISMA%202009%20checklist.doc checklist], a [http://www.prisma-statement.org/documents/PRISMA%202009%20flow%20diagram.doc template for a flow diagram], and their [http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097 guidelines]. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.&lt;br&gt;<br /> Finally, the APA web page, especially the [https://apastyle.apa.org/jars Journal Article Reporting Standards] for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantative methods], also give helpful advice and a checklist what should be included in a [https://apastyle.apa.org/jars/quant-table-9.pdf meta-analysis].&lt;br&gt;<br /> <br /> ==Experimental design==<br /> The following [[Media:ExperimentalDesign.pdf|lecture]] gives an introduction into experiments as a method to explore cause-effect-relationships, different types of validity related to the experiments and what might be threats to these types of validity. The first part explores the concept of causation, how cause-effect-relationships can be explored using experimental methods, and what the conditions for generalizing the cause-effect-relationship (explored in the experiment). The second part concentrates on the validity types related to the experiment: internal and statistical conclusion validity. The third part focusses on validity types related to the generalizability of the findings from an experiment: external and construct validity.<br /> <br /> ==Preparing physiological and neurophysiological measurements==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> =Preparing and conducting your study=<br /> ==Experiments==<br /> [[e-prime]]&lt;br&gt;<br /> [[Media:PsychoPy.pdf|PsychoPy]]&lt;br&gt;<br /> [[Web experiments]]&lt;br&gt;<br /> <br /> ==Questionnaires==<br /> [https://it.uib.no/Sp%C3%B8rreunders%C3%B8kelser_-_verkt%C3%B8y_for_utvikling,_utsending_og_analyse SurveyXact] (web questionnaire; licensed for UiB)&lt;br&gt;<br /> [https://pavlovia.org/ Pavlovia] (a web interface to run experiments created in PsychoPy)&lt;br&gt;<br /> [https://www.helsebiblioteket.no/psykisk-helse/skaringsverktoy Helsebibliotek] (health-related questionnaires)&lt;br&gt;<br /> <br /> ==Acquisition of qualitative / mixed-method data==<br /> TBA<br /> <br /> ==Collecting physiological and neurophysiological data==<br /> ===Physiological measurements===<br /> TBA<br /> <br /> ===Neurophysiological measurements: EEG===<br /> TBA<br /> <br /> ===Neurophysiological measurements: MRI===<br /> TBA<br /> <br /> ==Communicating with your participants==<br /> TBA<br /> <br /> ==Conducting your research in accordance with legal requirements==<br /> The following [[Media:Ethics_and_data_protection.pdf|lecture]] describes some practical considerations regarding research ethics and data protection. It includes some overview about ethical principles, how and from whom to obtain informed consent, an overview about data protection regulations for research data, a discussion which studies have to be approved by the regional research ethics committee (REK) or the Norwegian Data Protection Agency for Research Data (NSD) and what documents to include in such applications.<br /> <br /> =Analyzing your data=<br /> <br /> ==Learning and exploring statistics==<br /> A lot of statistics and what makes learning it and dealing with it so difficult is that it is based on quite abstract assumptions. For example, it is often difficult to grasp that distributions that statistical tests are based upon (e.g., t, F or χ² (chi-square) distributions) are a mathematical description (i.e., a formula) that is based upon empirical distributions (e.g., having an incredibly large number of trials with tossing a coin or throwing a dice). [https://garthtarr.com/about/ Dr. Garth Tarr] developed an [http://statstar.io/ incredibly helpful web page] where students can play around with, e.g., how the mean and the standard deviation a sample of N=20 could look like if an experiment in this group is repeated again and again or how likely outliers are and how this can influence whether a statistical test becomes significant or not.<br /> <br /> ==Organizing and storing your data==<br /> TBA&lt;br&gt;<br /> <br /> ==Evaluation methods==<br /> ===Extracting data===<br /> This [[Media:Shell-Programming.pdf|presentation]] provides an overview how shell scripts can be used to extract data from log files. The commands in the presentation can be tested using these [[Media:Materials.zip|example data]].<br /> <br /> ===Quantitative data analyses===<br /> <br /> TBA: an introduction into general statistical concepts<br /> [[:File:CrashCourseRefresher_Concepts.pdf]]<br /> <br /> When choosing your evaluation method, a key criterion is whether your variables (predictor/independent and outcome/dependent) are categorical or continuous. Most analysis methods are parametric statistics (i.e., they rely on the assumption that the data are drawn from a distribution, e.g., a standard normal distribution) and based upon the [https://en.wikipedia.org/wiki/General_linear_model General linear model]. <br /> <br /> TBA: Uni- and bivariate analyses<br /> [[:File:CrashCourseRefresher_jamovi_Analyses.pdf]]<br /> To explore the relationship between categorical predictor and categorical outcome variables, we use [[Media:FrequencyAnalyses.pdf|Frequency analyses]].&lt;br&gt;<br /> &lt;br&gt;<br /> <br /> [[Correlation and regression analysis]] can be used to explore the relationship between continuous predictor and continuous outcome variables. Logistic regression, where the relationship between continuous predictor and categorical outcome variables is explored, is a special case of the regression.&lt;br&gt;<br /> To explore the relationship between categorical predictor and continuous outcome variables, we use [[t-test and Analysis of Variance (ANOVA)]]. It is (in an ANCOVA) also possible to include continuous predictor variables, however the main focus in those analyses is typically on the categorical predictors as those represent the experimentally manipulated variables (e.g., treatment vs. control group).&lt;br&gt;<br /> &lt;br&gt;<br /> <br /> For a couple of years ago, we have changed from SPSS to jamovi for teaching. [https://www.jamovi.org/ jamovi] is a statistics package that is based upon R and quite similar in functionality to SPSS. For further information, please consult the [https://jamovi.readthedocs.io jamovi-documentation] which is available in several languages such as [https://jamovi.readthedocs.io/en/latest/ English], [https://jamovi.readthedocs.io/de/latest/ German], and [https://jamovi.readthedocs.io/no/latest/ Norwegian].&lt;br&gt;<br /> <br /> ===Qualitative or mixed-method analyses===<br /> TBA<br /> <br /> ==Literature review and meta-analysis==<br /> An overview on literature search is given at the [[#Literature search|top of this page]].<br /> <br /> ===Types of literature reviews===<br /> TBA<br /> <br /> ===Meta-analysis===<br /> TBA<br /> <br /> =Summarizing and publishing your study=<br /> ==Obeying the standards of the APA publication manual==<br /> A series of lectures dealt with how to obey the standards of the APA publication manual:<br /> The [[Media:APA-Introduction_-_Session_1.pdf|first lecture]] explores the questions: Why publishing? Why a rule system? before turning to the structure of a manuscript, proper language use and some mechanics of style (i.e., the use of period (.), comma, abreviations, parentheses, etc.).<br /> The [[Media:APA-Introduction_-_Session_2.pdf|second lecture]] shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.<br /> The [[Media:APA-Introduction_-_Session_3.pdf|third lecture]] demonstrates why, when and how to use references.<br /> The [[Media:APA-Introduction_-_Session_4.pdf|fourth lecture]] gives practical hints for writing manuscripts and term papers, gives and overview how the publication process works and discusses ethical issues with publication (authorship, consent, plagiarism).&lt;br&gt;<br /> Recently, the 6th edition of the APA-manual has been replaced by the [https://apastyle.apa.org/products/publication-manual-7th-edition 7th edition]. The amount of changes was rather moderate (summarized in a [[APA6_7_Changes|list with the most notable changes]]).&lt;br&gt;<br /> APA also provides the [https://apastyle.apa.org/ APA-style web page] with plenty of [https://apastyle.apa.org/style-grammar-guidelines very helpful information], incl. a steadily increasing numbers of examples, e.g., for [https://apastyle.apa.org/style-grammar-guidelines/paper-format/sample-papers papers], [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-figures figures] and [https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables tables], and for [https://apastyle.apa.org/style-grammar-guidelines/references/examples references]. The web page also provides what should be included in a manuscript, denoted as [https://apastyle.apa.org/jars Journal Article Reporting Standards (JARS)]. JARS includes three checklists for manuscripts using [https://apastyle.apa.org/jars/quant-table-1.pdf quantitative], [https://apastyle.apa.org/jars/quant-table-1.pdf qualitative] and [https://apastyle.apa.org/jars/mixed-table-1.pdf mixed-method] approaches (in addition there are specific checklists,. e.g., for [https://apastyle.apa.org/jars/quant-table-9.pdf quantitative] and [https://apastyle.apa.org/jars/qual-table-2.pdf qualitative] meta-analyses).&lt;br&gt;<br /> Please note that there is also an [https://www.unit.no/tjenester/norsk-apa-referansestil official recommendation / standard] on how to use the APA-style in Norwegian.&lt;br&gt;<br /> <br /> ==Presenting your results==<br /> This [[Media:Presentation_technique.pdf|lecture]] deals with how to present, covering topics such as the structure of a presentation and the use of graphics as well as personal factors such as dealing with nervousness.<br /> <br /> ==Software==<br /> [[Open source|What is open source software, why should you use it and what software packages are available for standard tasks (office suites, working with graphics, doing statistics)]]&lt;br&gt;<br /> [[Reference management]]&lt;br&gt;<br /> [[LaTeX]]&lt;br&gt;<br /> [[Tips and tricks|Tips and tricks for standard programmes]]&lt;br&gt;</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:CrashCourseRefresher_jamovi_Analyses.pdf&diff=305 2023-02-06T17:52:33Z

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Sje025 http://psychmethods.wiki.uib.no/index.php?title=T-test_and_Analysis_of_Variance_(ANOVA)&diff=303 2023-02-06T17:51:10Z

<p>Sje025: </p> <hr /> <div>=Using jamovi=<br /> The [[Media:AnalysisOfVariance_jamovi_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts).<br /> <br /> For an introduction from another perspective, you can head to [https://lsj.readthedocs.io/en/latest/Ch13/Ch13_ANOVA.html chapter 13] and [https://lsj.readthedocs.io/en/latest/Ch14/Ch14_ANOVA2.html chapter 14] of “learning statistics with jamovi” or to a [https://www.youtube.com/watch?v=GcbMG6sizXs&amp;list=PLkk92zzyru5OAtc_ItUubaSSq6S_TGfRn&amp;index=30 video introduction] by Barton Poulson from datalab.cc.<br /> <br /> =Using SPSS=<br /> The [[Media:AnalysisOfVariance_SPSS_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).&lt;br&gt;<br /> The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.<br /> <br /> In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf|additional assignments]], and two further ZIP-files accompanying it: [[Media:DataFiles_Field_TabachnikFidell.zip|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.<br /> <br /> =More in-depth on the theoretical background=<br /> Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.&lt;br&gt;<br /> The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik &amp; Fidell (2013), Ch. 6, 7, 8).</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=T-test_and_Analysis_of_Variance_(ANOVA)&diff=302 2023-02-06T17:47:39Z

<p>Sje025: </p> <hr /> <div>=Using jamovi=<br /> The [[Media:AnalysisOfVariance_jamovi_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts).<br /> <br /> =Using SPSS=<br /> The [[Media:AnalysisOfVariance_SPSS_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).&lt;br&gt;<br /> The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.<br /> <br /> In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf|additional assignments]], and two further ZIP-files accompanying it: [[Media:DataFiles_Field_TabachnikFidell.zip|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.<br /> <br /> =More in-depth on the theoretical background=<br /> Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.&lt;br&gt;<br /> The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik &amp; Fidell (2013), Ch. 6, 7, 8).</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=T-test_and_Analysis_of_Variance_(ANOVA)&diff=301 2023-02-06T17:45:43Z

<p>Sje025: </p> <hr /> <div>=Using jamovi=<br /> The [[Media:AnalysisOfVariance_jamovi_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts).<br /> <br /> =Using SPSS=<br /> The [[Media:AnalysisOfVariance_SPSS_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).&lt;br&gt;<br /> The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.<br /> <br /> In addition, there is a file with [[Media:AnalysisOfVariance_SPSS_Assignment.pdf|additional assignments]], and two further ZIP-files accompanying it: [[Media:DataFiles.zip|The first]] contains the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip|the other]] contains SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.<br /> <br /> =More in-depth on the theoretical background=<br /> Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.&lt;br&gt;<br /> The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB.zip|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik &amp; Fidell (2013), Ch. 6, 7, 8).</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=T-test_and_Analysis_of_Variance_(ANOVA)&diff=300 2023-02-06T17:43:37Z

<p>Sje025: </p> <hr /> <div>=Using jamovi=<br /> The [[Media:AnalysisOfVariance_jamovi_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts).<br /> <br /> =Using SPSS=<br /> The [[Media:AnalysisOfVariance_SPSS_Lecture.pdf|lecture]] briefly introduces how different variable types determine which statistical methods can be used, what assumptions determine when parametric statistical tests can be used (and which procedures can be used to test these assumptions). The Analysis of Variance (ANOVA) is introduced starting with some background information and how to do a simple ANOVA manually (in Excel), followed by more extensive background information (such as typical designs, contrasts). Finally, more complex ANOVA models are introduced, starting with Analysis of Covariance (ANCOVA) over the multivariate forms (MANOVA and MANCOVA) to an application of these multivariate forms in profile analysis (e.g., for tracing development over time or distinguishing between subtests within a larger test battery).&lt;br&gt;<br /> The [[Media:AnalysisOfVariance_SPSS_Exercise.pdf|PC-exercise]] deals with the practical aspects of carrying out Analyses of Variance in SPSS. The exercise begins with a brief introduction on the preparation of one's data (e.g., file organization, hot to treat missing values, etc.), then demonstrates the equivalence of a t-test with a univariate ANOVA (if there is only one predictor with two steps), how multiple predictors / factors can be included in the ANOVA (incl. continuous predictors in an ANCOVA) and how multivariate dependent variables can modelled (MANOVA) to the use of the MANOVA within repeated-measures ANOVA and Profile analysis. This is followed by an assignment to test the acquired knowledge practically.<br /> <br /> In addition, there is a file with [[Media:Analysis_of_Variance_-_Assignment.pdf|additional assignments]] and the [[Media:Analysis_of_Variance_-_Assignment_-_Solution.pdf|solutions]] to it.<br /> <br /> Finally, there are two ZIP-files: [[Media:DataFiles.zip|One]] with the data files required in the exercise and the assignment, [[Media:AnalysisOfVariance_SPSS_SyntaxOutput.zip|another]] containing SPSS syntax (with comments) and SPSS output files for the analyses described in the lecture slides as well as for the additional assignments.<br /> <br /> =More in-depth on the theoretical background=<br /> Both lecture slides include practical examples for calculation: A [[Media:AnalysisOfVariance_Step-by-step.ods|LibreOffice/Excel-file]] with a demonstration how a very simple ANOVA (with one three-step factor; example from Field (2018), Ch. 12) is calculated by hand.&lt;br&gt;<br /> The slides on SPSS further contain a [[Media:AnalysisOfVariance_ExamplesMATLAB.zip|ZIP file]] to run a several ANOVA models (ANCOVA, MANOVA and a profile analysis) in MATLAB / Octave (from Tabachnik &amp; Fidell (2013), Ch. 6, 7, 8).</div>

Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:AnalysisOfVariance_ExamplesMATLAB_TabachnikFidell.zip&diff=299 2023-02-06T17:42:58Z

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Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:AnalysisOfVariance_SPSS_Exercise.pdf&diff=298 2023-02-06T17:39:48Z

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Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:AnalysisOfVariance_Step-by-step.ods&diff=297 2023-02-06T17:38:02Z

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Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:AnalysisOfVariance_SPSS_SyntaxOutput.zip&diff=296 2023-02-06T17:38:01Z

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Sje025 http://psychmethods.wiki.uib.no/index.php?title=File:AnalysisOfVariance_SPSS_Lecture.pdf&diff=295 2023-02-06T17:38:00Z

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Sje025