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

Linear Mixed Models and Estimation Techniques

Linear mixed models (LMMs) serve as a versatile statistical framework, combining fixed effects that capture the overall trends with random effects that account for variability across subjects, ...
JSTOR Daily

High-Breakdown Inference for Mixed Linear Models

Mixed linear models are used to analyze data in many settings. These models have a multivariate normal formulation in most cases. The maximum likelihood estimator (MLE) or the residual MLE (REML) is ...
JSTOR Daily

Bayesian Prediction of Spatial Count Data Using Generalized Linear Mixed Models

Spatial weed count data are modeled and predicted using a generalized linear mixed model combined with a Bayesian approach and Markov chain Monte Carlo. Informative priors for a data set with sparse ...
technologynetworks

Linear Regression

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...