GESIS Training Courses

Course 8: Meta-Analysis in Social Research and Survey Methodology

Dr. Bernd Weiß, Jessica Daikeler

Datum: 20.08 - 24.08.2018 ics-Datei

Referenteninformationen - Dr. Bernd Weiß

Referenteninformationen - Jessica Daikeler


This course will provide an introduction to a broad range of meta-analytical techniques using the free statistical software package R. Meta-analysis can be thought of as a collection of statistical analyses used to examine results from individual studies with the general purpose of integrating their findings. A meta-analysis is considered to be the statistical part of a so-called systematic review. While the course focuses particularly on the statistical aspects of a systematic review, we briefly introduce all parts of a research synthesis. That is, we will also discuss how to formulate a research question, search and evaluate the literature as well as how to extract and code the data. In this course we will cover the basics of meta-analysis as well as more advanced topics. However, we will not be able to cover topics like network meta-analysis or meta-analytic structural equation modeling. Participants are not expected to have a working knowledge of R but are provided with an R introduction. Special emphasis will be put on performing meta-analysis on experimental and intervention-based studies, in particular from survey methodology. This course is approved by the Campbell Collaboration (
For a full length syllabus of this course, please click here.



Participants will find the course useful if:
  • they are interested in conducting their own research synthesis, especially using the free software package R;
  • they want to gain a better understanding of the pros and cons of the method when evaluating meta-analytical results;
  • they consider to prepare a Master thesis, a PhD thesis, or a scientific publication in social sciences or survey methodology using quantitative research synthesis methods.


By the end of the course participants will:
  • be able to determine whether their research problem can be analyzed with a meta-analysis;
  • have gained a thorough understanding of how to conduct a meta-analysis and how to present the results of a meta-analysis; most importantly they have learned to avoid typical pitfalls when performing a meta-analysis;
  • have learned how to conduct a basic meta-analysis using the free software package R and R's metafor package.


  • Participants are expected to have a good working knowledge of statistics at an undergraduate level, e.g. statistical inference (standard error, confidence interval), bivariate statistics (correlation coefficient, mean differences, odds ratio) as well as a basic understanding of (linear) regression analysis and ANOVA.
  • Participants are interested in any subtopic in social research or survey methodology.
  • During the course the statistical software package R will be used, which should be installed on participants computers. A brief introduction will be given in the first afternoon session.