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Exploratory assessment of treatment-dependent random-effects distribution using gradient functions

Imai, Takumi 京都大学 DOI:10.14989/doctor.r13422

2021.05.24

概要

In analyzing repeated measurements from randomized controlled trials with mixed-effects models, it is important to carefully examine the conventional normality assumption regarding the randomeffects distribution and its dependence on treatment allocation in order to avoid biased estimation and correctly interpret the estimated random-effects distribution. In this paper, 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 randomeffects distribution on covariates, or for finding the subpopulations in the random effects.

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参考文献

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