Install R!

R is freely available here from the “Comprehensive R Archival Network” (CRAN).

Note that the “base R” program that you get from the above link can work as a standalone analysis software, but we strongly recommend using a program like RStudio to make your life easier. RStudio is the most popular, feature-rich, and user-friendly way to interact with R and develop your R scripts.

Learn About R!

There is a vertiable trove of introductory R resources on the Internet, but below are several resources you might find especially helpful if you’re new to R. Bear in mind that most questions about R have already been answered by someone somewhere on the web, so Google will be your best friend as you set out on your R journey.

Find Cool Packages for R!

After installing R and learning the basics, it’s time to explore the vast world of user-developed R packages. There are thousands of packages available for R, but below are some of our favorites (other than psychmeta, of course!). You can also find a complete list of the R packages hosted on CRAN here.


The tidyverse package is actually a collection of packages that can help with data importation, data cleaning, data management, creating beautiful plots, and much more.


The metafor package is the most popular package for (non-psychometric) meta-analysis in R. It has great tools for computing meta-regressions, doing publication-bias analyses, and plotting meta-analytic results. Note that “escalc” objects generated by psychmeta’s meta-analysis functions are compatible with metafor so that you can flexibly analyze your data.


The psych package is a collection of resources for psychologists and has wonderful functions for factor analysis, reliability analysis, item analysis, and much more.


The apaTables package is a great help for doing reproducible analyses in R. It can export R analyses to Word-format APA-style tables for common types of analyses (e.g., regression models, ANOVAs, correlation matrices).

Explore More Meta-Analysis Tools for R!

If you’d like to explore more R packages for meta-analysis, check out CRAN’s meta-analysis task view.