The Relative Benefits of Meta-Analysis Conducted With Individual Participant Data Versus Aggregated Data

TLDR: The authors describe the relative benefits of conducting meta-analyses with (a) individual participant data (IPD) gathered from the constituent studies and (b) aggregated data (AD), or the group-level statistics that appear in reports of a study's results.

Abstract: The authors describe the relative benefits of conducting meta-analyses with (a) individual participant data (IPD) gathered from the constituent studies and (b) aggregated data (AD), or the group-level statistics (in particular, effect sizes) that appear in reports of a study's results. Given that both IPD and AD are equally available, meta-analysis of IPD is superior to meta-analysis of AD. IPD meta-analysis permits synthesists to perform subgroup analyses not conducted by the original collectors of the data, to check the data and analyses in the original studies, to add new information to the data sets, and to use different statistical methods. However, the cost of IPD meta-analysis and the lack of available IPD data sets suggest that the best strategy currently available is to use both approaches in a complementary fashion such that the first step in conducting an IPD meta-analysis would be to conduct an AD meta-analysis. Regardless of whether a meta-analysis is conducted with IPD or AD, synthesists must remain vigilant in how they interpret their results. They must avoid ecological fallacies, Simpson's paradox, and interpretation of synthesis-generated evidence as supporting causal inferences.