Comparing methods to assess treatment effect heterogeneity in general parametric regression models
Abstract
This paper reviews and compares methods to assess treatment effect heterogeneity in the context of parametric regression models. These methods include the standard likelihood ratio tests, bootstrap likelihood ratio tests, and Goeman's global test motivated by testing whether the random effect variance is zero. We place particular emphasis on tests based on the score-residual of the treatment effect and explore different variants of tests in this class. All approaches are compared in a simulation study, and the approach based on residual scores is illustrated in a clinical trial with time-to-event outcome comparing treatment versus placebo. Our findings demonstrate that score-residual based methods provide practical, flexible and reliable tools for exploring treatment effect heterogeneity and treatment effect modifiers, and can provide useful guidance for decision making around treatment effect heterogeneity.
Cite
@article{arxiv.2503.22548,
title = {Comparing methods to assess treatment effect heterogeneity in general parametric regression models},
author = {Yao Chen and Sophie Sun and Konstantinos Sechidis and Cong Zhang and Torsten Hothorn and Björn Bornkamp},
journal= {arXiv preprint arXiv:2503.22548},
year = {2026}
}