I am conducting a meta-analysis on 20 studies. The outcome of interest in each study is represented by a proportion/percentage. The sample size n is known and is different for each study. I have three aims:
- To realize a pooled analysis in order to calculate a summary effect (a weighted proportion)
- To calculate heterogeneity across the studies
- To explore this heterogeneity by considering potential effect modifiers in a meta-regression analysis
Can someone help me in identifying the more correct method to realize all this in STATA or R? Thank you!
Best Answer
This is a meta-analysis of proportions. Just as you mentioned, the m-a of proportions is a little different than other types of meta-analysis- it includes studies that do not use controls. You can use R to do a meta-analysis of proportions. I recently made a tutorial on that on YouTube and shared my code on Github. This hands-on tutorial provides a step-by-step guide showing you how to conduct a full meta-analysis of proportions, including all the goals you mentioned in your post. My code allows you to conduct your analysis with either the logit transformation or double-arcsine transformation. You can also do it without transformation using my code. The R script shown in the video is readily adaptable for you to use for your own analyses.
Check out the tutorial here: https://youtu.be/2wbXTFvaRnM.
Download my code here: https://github.com/wnk4242/meta-analysis-of-proportions