3.1 What should be in the file

To conduct Meta-Analyses in R, you need to have your study data prepared. In primary analysis, you might have a file with rows for people, and columns for variables. In meta-analysis, you will have a file with a row for each effect size. The columns often include the following information:

• The names of the individual studies, so that they can be easily identified later on. You can use the full reference, or just the first author and publication year of a study (e.g. “Ebert et al., 2018”)
• The calculated effect size of the study (either Cohen’s d or Hedges’ g, or some other form of effect size
• The Standard Error (SE) or sampling variance of the calculated effect
• Often, you do not have the effect size and the variance of the effect size yet. In that case, you need the statistics required to compute it. This could be:
  • The correlation coefficient and number of participants (N)
  • The Mean of both the Intervention and the Control group at the same assessment point
  • The Standard Deviation of both the Intervention and the Control group at the same assessment point
  • The number of participants (N) in each group of the trial
• Any coded moderators. E.g., if you want to have a look at differences between various study subgroups later on, you also need a subgroup code for each study which signifies to which subgroup it belongs. For example, if a study was conducted in children, you might give it the subgroup code “children”. Continuous moderators can be included in the same way; e.g., the proportion of men in the sample.

Working with R, the easiest way is often to store data in EXCEL spreadsheets, but R can read nearly any input format. Google is your friend.

One advantage of using an R project is that the project directory is automatically set as the working directory. Just copy your data file to the folder that contains the “.Rproj” file, and you will be able to load files by name.