insider.si.edu

Linear mixed models : a practical guide using statistical software / Brady T. West, Kathleen B. Welch, Andrzej T. Gałecki, University of Michigan, Ann Arbor, USA ; with ...

"First edition published in 2006." 1. Introduction -- What are linear mixed models (LMMs)? -- Models with random effects for clustered data -- Models for longitudinal or repeated-measures data -- A ...
Nature

Warped linear mixed models for the genetic analysis of transformed phenotypes

Linear mixed models (LMMs) are a powerful and established tool for studying genotype–phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a ...
Nature

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population ...
JSTOR Daily

Power and Sample Size for Fixed-Effects Inference in Reversible Linear Mixed Models

Despite the popularity of the general linear mixed model for data analysis, power and sample size methods and software are not generally available for commonly used test statistics and reference ...
Simon Fraser University

Analysis of Variance for Mixed and Random Effect Models

Just as PROC GLM is the flagship procedure for fixed-effect linear models, the MIXED procedure is the flagship procedure for random- and mixed-effect linear models. PROC MIXED fits a variety of mixed ...
JSTOR Daily

Missing Covariates in Longitudinal Data with Informative Dropouts: Bias Analysis and Inference

We consider estimation in generalized linear mixed models (GLMM) for longitudinal data with informative dropouts. At the time a unit drops out, time-varying covariates are often unobserved in addition ...