Meta‐analysis using individual participant data: one‐stage and two‐stage approaches, and why they may differ

By D. Burke, J. Ensor, R. Riley. Statistics in Medicine, 2016

468 citations recorded by the source corpus.

Meta‐analysis using individual participant data (IPD) obtains and synthesises the raw, participant‐level data from a set of relevant studies. The IPD approach is becoming an increasingly popular tool as an alternative to traditional aggregate data meta‐analysis, especially as it avoids reliance on published results and provides an opportunity to investigate individual‐level interactions, such as treatment‐effect modifiers. There are two statistical approaches for conducting an IPD meta‐analysis: one‐stage and two‐stage. The one‐stage approach analyses the IPD from all studies simultaneously, for example, in a hierarchical regression model with random effects. The two‐stage approach derives aggregate data (such as effect estimates) in each study separately and then combines these in a traditional meta‐analysis model. There have been numerous comparisons of the one‐stage and two‐stage approaches via theoretical consideration, simulation and empirical examples, yet there remains confusion regarding when each approach should be adopted, and indeed why they may differ.

Subfields: Experimental and Cognitive Psychology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/87618d016e8d549d9ef738eba6ff34378bb66c05

Citations in the corpus

• The effect of a single dose of intravenous ketamine on suicidal ideation: a systematic review and individual participant data meta-analysis (2017, unknown): “We used a standard one-stage hierarchical modeling approach (19), with participants nested within studies.”
• Are women more generous than men? A meta-analysis (2021, unknown): “As Burke et al. (2017) note, these methods in general produce similar results and differences largely occur when researchers use different modelling assumptions.”