In analyzing repeated measurements from randomized controlled trials with mixed‐effects models, it is important to carefully examine the conventional normality assumption regarding the random‐effects distribution and its dependence on treatment allocation in order to avoid biased estimation and correctly interpret the estimated random‐effects distribution. In this article, we propose the use of a gradient function method in modeling with the different random‐effects distributions depending on the treatment allocation. This method can be effective for considering in advance whether a proper fit requires a model that allows dependence of the random‐effects distribution on covariates, or for finding the subpopulations in the random effects.

中文翻译：

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使用梯度函数探索性评估依赖治疗的随机效应分布

在分析具有混合效应模型的随机对照试验的重复测量结果时，重要的是仔细检查有关随机效应分布及其对治疗分配的依赖性的常规正态性假设，以避免产生偏倚的估计并正确解释估计的随机效应分配。在本文中，我们建议使用梯度函数方法在建模中根据治疗分配确定不同的随机效应分布。这种方法对于预先考虑适当的拟合是否需要允许随机效应分布依赖于协变量的模型或寻找随机效应中的亚群可能是有效的。