Subgroup analysis is the process of comparing a treatment effect for two or more variants of an intervention—to ask, for example, if an intervention’s impact is affected by the setting (school versus community), by the delivery agent (outside facilitator versus regular classroom teacher), by the quality of delivery, or if the long-term effect differs from the short-term effect. While large-scale studies often employ subgroup analyses, these analyses cannot generally be performed for small-scale studies, since these typically include a homogeneous population and only one variant of the intervention. This limitation can be bypassed by using meta-analysis. Meta-analysis allows the researcher to compare the treatment effect in different subgroups, even if these subgroups appear in separate studies. We discuss several statistical issues related to this procedure, including the selection of a statistical model and statistical power for the comparison. To illustrate these points, we use the example of a meta-analysis of obesity prevention.
KeywordsMeta-analysis Research synthesis Systematic review Subgroups Subgroup analysis Fixed-effect Fixed-effects Random-effects
The ideas expressed in this paper reflect the many discussions that took place among ourselves, Larry Hedges, and Hannah Rothstein while we were working on the text “Introduction to Meta-Analysis” and on the computer program “Comprehensive Meta-Analysis.” We are grateful for Larry’s and Hannah’s many insights, their generosity, and their friendship. Dr. Borenstein was funded in part by the following grants from the National Institute on Drug Abuse: “Forest Plots for Meta-Analysis” (DA019280) under the direction of Dr. Thomas Hilton, “Power Analysis for Meta-Analysis” (DA022799), and “Power Analysis for Cluster Randomized Trials” (DA025366) under the direction of Dr. Augusto (Augie) Diana. Prof. Higgins was funded in part by Grant U105285807 from the UK Medical Research Council.
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