4.5 Editorial Material

Comment: Diagnostics and Kernel-based Extensions for Linear Mixed Effects Models with Endogenous Covariates

Journal

STATISTICAL SCIENCE
Volume 35, Issue 3, Pages 396-399

Publisher

INST MATHEMATICAL STATISTICS
DOI: 10.1214/20-STS782

Keywords

Linear mixed models; partial likelihood; conditional independence test; marginal effects; kernel mixed models

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We discuss Linear mixed models with endogenous covariates: modeling sequential treatment effects with application to a mobile health study by Qian, Klasnja and Murphy. In this discussion, we study when the linear mixed effects models with endogenous covariates are feasible to use by providing examples and diagnostic tools as well as discussing potential extensions. This includes evaluating feasibility of partial likelihood-based inference, checking the conditional independence assumption, estimation of marginal effects, and kernel extensions of the model.

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