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.

翻译：本文综述并比较了在参数回归模型背景下评估处理效应异质性的方法。这些方法包括标准似然比检验、自助法似然比检验，以及由检验随机效应方差是否为零所启发的Goeman全局检验。我们特别强调基于处理效应得分残差的检验，并探讨了此类检验的不同变体。所有方法均通过模拟研究进行比较，并在一项比较治疗组与安慰剂组、以事件发生时间为结局的临床试验中，阐述了基于残差得分的方法。我们的研究结果表明，基于得分残差的方法为探索处理效应异质性及处理效应修饰因子提供了实用、灵活且可靠的工具，并能为围绕处理效应异质性的决策提供有益的指导。