# Psychological Methods: Wiki

## Contents

# Planning your study

## Literature search

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).

## Experimental design

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 and conducting your study

## Experiments

e-prime

PsychoPy

Web experiments

## Questionnaires

Web questionnaires (SurveyXact)

## Communicating with you participants

TBA

# Analyzing your data

## Organizing and storing your data

TBA

## Evaluation methods

### Extracting data

This 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 example 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.

t-test and Analysis of Variance (ANOVA) can be used to explore the relationship between categorical predictor and continuous outcome variables. 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).

### Qualitative or mixed-method analyses

TBA

## Literature review and meta-analysis

An overview on literature search is given at the top of this page.

### Types of literature reviews

TBA

### Meta-analysis

TBA

# 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).

## Software

What is open source software, why should you use it and what packages can be used for standard tasks (office suites, working with graphics, statistic packages)

Reference management

LaTeX

Tips and tricks for standard programmes