Description
This course provides the conceptual, methodological, and operational knowledge required to perform high-quality meta-analyses inspired by top-tier academic journals.
Course tailored to Ph.D. students seeking to produce a meta-analysis (for their dissertation or other projects). Students will have developed the first draft of a manuscript, including data and analysis, that could be developed further if aiming for publication. The class is relevant to business disciplines at large. Specifically, it covers material drawn from management, marketing, (health) economics, IT, HR, psychology, and medicine.
The class is a mix between acquiring foundation knowledge while also facilitating the application of this knowledge in a research project that is carried out throughout the semester. Each week features 1) seminar-type discussions of key methodological and substantive articles that have applied these methodological concepts, 2) short lecture-type conceptual presentations, and 3) presentations of the students' own meta-analysis projects. Students will also learn to operate an open-source software.
Themes covered
- History of meta-analysis
- Epistemological foundations of meta-analysis
- Types of meta-analyses
- Using the R software
- How to perform meta-analysis including the following themes (non-exhaustive list) :
+ Selecting articles to include in the meta-analysis;
+ Effect size;
+ Fixed vs random effect models;
+ Moderators;
+ Data-dependency;
+ Coding, coding booklet, double coding, rater reliability;
+ Meta-regression, multi-level meta-analysis, meta-SEM;
+ Psychometric meta-analysis;
+ Meta-analysis of longitudinal studies.
