A note on the bias of standard errors when orthogonality of mean and variance parameters is not satisfied in the mixed model for repeated measures analysis

DOI10.1002/SIM.8474zbMATH Open1546.62524MaRDI QIDQ6627323

Yusuke Yamaguchi, Masaaki Doi, [[Person:6067160|Author name not available (Why is that?)]], Kazushi Maruo, Masahiko Gosho

Publication date: 29 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

longitudinal datastatistical softwaremodel misspecificationmissingrandomized clinical trial

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• A Covariance Estimator for GEE with Improved Small‐Sample Properties
• Likelihood based frequentist inference when data are missing at random
• Asymptotic Inference with Incomplete Data
• Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data
• A Note on the Efficiency of Sandwich Covariance Matrix Estimation
• Clinical Trials with Missing Data
• Maximum Likelihood Estimation of Misspecified Models

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Issues with the expected information matrix of linear mixed models provided by popular statistical packages under missingness at random dropout

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