Provide my students with a tool for creating forest plots, funnel plots and other elements of meta-analysis in two sessions.
Most students were gearing up to do a meta-analysis for the first time based on a clinical question of interest to them. They'd previously had an introductory lecture on meta-analsis but none had any experience with R.
Two descriptive R scripts that can be used by those with no previous experience with R. The first, analysis/basic_operations.R, is a gentle, hands-on introduction to some basic concepts in R, such as creating and manipulating objects. The other, analysis/meta-analysis-example.R, introduces some basic functions of the wonderful and easy-to-use meta package (Schwarzer, 2007).
Both scripts can be dowloaded from the analysis folder above. The data file used in the meta-analysis example can be downloaded from the analysis/data folder. There are also two short documents in the handouts folder: (1) instructions for downloading and installing R and RStudio and (2) some resources for doing meta-analysis with R. Hope you find them useful. One of the forest plots from the second R script can be seen below.
My original motivation for learning R was not to do statistical analysis but to produce beautiful graphs. Having learned SPSS as an undergraduate, I'd been using it ever since--and never liked its graphs aesthetically. When I learned that the graphs I'd seen were produced with R and its ggplot2 package (Wickham, 2016), I never looked back.
The lesson here is to approach R with a specific purpose in mind, such as How can I make a graph like that? or What can I use to do a meta-analysis and make a good-looking forest plot? Much better to learn R this way that by asking too broad a question like, How do I learn R? When it came time for me to teach my students how to do a meta-analysis, I decided the best tool for the job was R and its meta package. You can gradually "learn R" by approaching it one task at a time if your experience is anything like mine.
