Meta-Analyses & Systematic Reviews

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Workshop: A Practical Guide for Meta-Analyses in R

By Constantin Yves Plessen

What is this?

Excerpt from site: This blogpost is an adaption from my 90 minute workshop on all basic steps in conducting a meta-analysis in R. The audience of the original workshop were graduate psychology students at the University of Vienna with a focus on research methods. Most statistical and methodical elements were already discussed, yet the implementation in R was new to all of them. And programming in general was new to most of them. I therefore introduced R very shortly, before explaining the actual meta-analytical analyses more briefly. I added some explanations and references to make the file more self-explanatory for independent study. Therefore, this post also contains materials and references on how to install R, R Studio, and some basic concepts of programming.

  1. Post here: https://constantinyvesplessen.com/post/workshop_meta_analysis/
  2. Dataset and code here: https://osf.io/y9d2w/

R Code for Meta-Analysis Books

By Wolfgang Viechtbauer

What is this?

Excerpt from repo: This repo contains R code to reproduce the examples and illustrations from various books on meta-analysis.

The code is provided as R Markdown documents, which are rendered to HTML files. You can download the repo and open up the HTML files with your browser. Or you can look at the files online here: 1. Link to repo: https://github.com/wviechtb/meta_analysis_books

  1. Link to r code corresponding to “Practical Meta-Analysis by Lipsey and Wilson (2001)”: https://wviechtb.github.io/meta_analysis_books/lipsey2001.html
  2. Link to r code corresponding to “Introduction to Meta-Analysis by Borenstein et al. (2009)”: https://wviechtb.github.io/meta_analysis_books/borenstein2009.html
  3. Link to r code corresponding to “The Handbook of Research Synthesis and Meta-Analysis by Cooper et al. (2019)”: https://wviechtb.github.io/meta_analysis_books/cooper2019.html
  4. Link to r code corresponding to “Publication Bias in Meta-Analysis by Rothstein et al. (2005)”: https://wviechtb.github.io/meta_analysis_books/rothstein2005.html