Psychological Methods: Wiki
- 1 Planning your study
- 2 Preparing and conducting your study
- 2.1 Experiments
- 2.2 Questionnaires
- 2.3 Acquisition of qualitative / mixed-method data
- 2.4 Collecting physiological and neurophysiological data
- 2.5 Communicating with your participants
- 2.6 Conducting your research in accordance with legal requirements
- 3 Analyzing your data
- 4 Summarizing and publishing your study
Planning your study
The following 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 here for a more detailed overview).
There is also a fantastic introduction on 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.
On the PRISMA-web page will you find a checklist, a template for a flow diagram, and their guidelines. These materials should help and guide you when creating systematic reviews or a meta-analyses with high quality.
Finally, the APA web page, especially the Journal Article Reporting Standards for manuscripts using quantative methods, also give helpful advice and a checklist what should be included in a meta-analysis.
The following 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.
Preparing physiological and neurophysiological measurements
Neurophysiological measurements: EEG
Neurophysiological measurements: MRI
Preparing and conducting your study
SurveyXact (web questionnaire; licensed for UiB)
eSurvey Pro (web questionnaire)
LimeSurvey (web questionnaire)
Pavlovia (a web interface to run experiments created in PsychoPy)
Helsebibliotek (health-related, free questionnaires)
Acquisition of qualitative / mixed-method data
Collecting physiological and neurophysiological data
Neurophysiological measurements: EEG
Neurophysiological measurements: MRI
Communicating with your participants
Conducting your research in accordance with legal requirements
The following 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.
Analyzing your data
Learning and exploring statistics
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). Dr. Garth Tarr developed an 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.
Organizing and storing your data
Quantitative data analyses
When choosing your evaluation method a key criterion is whether you 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 General linear model.
Correlation and regression analysis can be used to explore the relationship between continuous predictor and continuous outcome variables.
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).
We recently changed from SPSS to jamovi for teaching. jamovi is a statistics package that is based upon R and quite similar in functionality to SPSS. I also run a couple of other Wikis on jamovi (in English, Norwegian, and German).
Qualitative or mixed-method analyses
Literature review and meta-analysis
An overview on literature search is given at the top of this page.
Types of literature reviews
Summarizing and publishing your study
Obeying the standards of the APA publication manual
A series of lectures dealt with how to obey the standards of the APA publication manual:
The 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.).
The second lecture shows how to display results in figures and tables and provides some practical hints to help with writing manuscripts.
The third lecture demonstrates why, when and how to use references.
The 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).
Recently, the 6th edition of the APA-manual has been replaced by the 7th edition. The amount of changes was rather moderate (summarized in a list with the most notable changes).
APA also provides the APA-style web page with plenty of very helpful information, incl. a steadily increasing numbers of examples, e.g., for papers, figures and tables, and for references. The web page also provides what should be included in a manuscript, denoted as Journal Article Reporting Standards (JARS). JARS includes three checklists for manuscripts using quantitative, qualitative and mixed-method approaches (in addition there are specific checklists,. e.g., for quantitative and qualitative meta-analyses).
Please note that there is also an official recommendation / standard on how to use the APA-style in Norwegian.
Presenting your results
This 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.
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)
Tips and tricks for standard programmes