Premium
Meta‐STEPP with random effects
Author(s) -
Wang Xin Victoria,
Cole Bernard,
Bonetti Marco,
Gelber Richard D.
Publication year - 2018
Publication title -
research synthesis methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.376
H-Index - 35
eISSN - 1759-2887
pISSN - 1759-2879
DOI - 10.1002/jrsm.1288
Subject(s) - covariate , random effects model , meta analysis , statistics , fixed effects model , outcome (game theory) , econometrics , mathematics , computer science , medicine , panel data , mathematical economics
We recently developed a method called Meta‐STEPP[1][Wang XV, 2016] based on the fixed‐effects meta‐analytic approach to explore treatment effect heterogeneity across a continuous covariate for individual time‐to‐event data arising from multiple clinical trials. Meta‐STEPP forms overlapping subpopulation windows (meta‐windows) along a continuous covariate of interest, estimates the overall treatment effect in each meta‐window using standard fixed‐effects method, plots them against the continuous covariate, and tests for treatment‐effect heterogeneity across the range of covariate values. Here, we extend this method using random‐effects methods and find it to be more conservative than the fixed‐effects method. Both the random‐ and fixed‐effects Meta‐STEPP are implemented in R .