[R-meta] Meta-Analysis and Forest Plot for Multiple Treatments and Outcomes
Ruth Appel
r@ppe| @end|ng |rom @t@n|ord@edu
Mon Jan 31 19:02:09 CET 2022
Hi all,
I’m currently conducting my first meta-analysis, an internal meta-analysis to summarize the result of 3 similar studies my colleagues and I conducted.
I looked at the documentation of various meta-analysis packages and tutorials, but I am still not fully sure about the best approach.
The experiments I’m analyzing all have a similar structure (2 treatment groups, 1 control group; 8 different outcomes (measuring different constructs)). The raw data has repeated measures, but we look at outcomes at the group level, so I calculated all necessary summary statistics (mean, sd, n).
My goal is to create a forest plot that shows Hedges’ g estimated using an FE model (because the studies were highly similar) for (1) all 3 studies individually and (2) across all studies. Ideally, the final result would be a single forest plot with individual study estimates and across study estimate grouped by outcome.
I managed to create such a plot with the meta package for the 2 treatment groups separately, but I realized that my SEs could be biased in this case because I’m not accounting for the correlations in the variance resulting from the comparison of two treatment groups to the same control group. Similarly, I found a workaround to show all outcomes in 1 forest plot by using subgroups for the different outcomes, but I do not take into consideration that outcomes might be correlated within studies. I also didn’t find a way to show the individual study results in addition to the overall network results in a forest plot of a netmeta object.
I then tried to calculate the correct values using metafor and following the tutorial at https://www.metafor-project.org/doku.php/analyses:gleser2009#multiple-treatment_studies, but it seems like the individual studies are not correctly identified in the output (the ids are all unique instead of matching the study variable I had created).
My questions are: (1) Did I overlook guidance somewhere on how to exactly specify a model like the one above using the metafor, meta (or another R) package, and generate a forest plot for it?
(2) If this is not easily possible, do you think the bias introduced should be sufficiently small such that acknowledging it and presenting separate meta-analyses for each treatment, and a network meta analysis with the overall effects of each treatment (separately for each outcome) in the appendix, is acceptable? (I had very similar estimates across all the approaches described above.)
Best regards, and thank you very much for your guidance,
Ruth
Ruth Elisabeth Appel
Ph.D. Candidate in Media Psychology
Stanford University Department of Communication
rappel using stanford.edu
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