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

Lecturers: Dr. Bernd Weiß, Jessica Daikeler

Date: 20-24 August 2018
Time: 09:00-13:00, 14:00-16:00

Short Course Description:

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 (https://www.campbellcollaboration.org).

Course Prerequisites:

  • 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.

    Target Group:

    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 preparing a Master thesis, a PhD thesis, or a scientific publication in social sciences or survey methodology using quantitative research synthesis methods.

    Course and Learning Objectives:

    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.

    Organizational Structure of the Course:

    The course will consist of 4 hours of lecture in the morning. Students will spend the afternoons working on exercises designed to deepen their understanding of the material. The instructors will be available in the afternoon to answer questions.

    Software and Hardware Requirements:

    Participants need to bring a laptop with R and RStudio installed. Since we will be installing additional R packages throughout the course, participants need to make sure that their laptop can access the internet. Also, they need to make sure that they can install R packages (e.g., after starting R, type in "install.packages("metafor")". If you receive the message "package ‘metafor’ successfully unpacked and MD5 sums checked", then everything works fine).