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, ...

Generalized linear mixed models (GLMM) are useful in a variety of applications. With surrogate covariate data, existing methods of inference for GLMM are usually computationally intensive. We propose ...

Keywords: Statistical analyses. Regression models. Post-earthquake ignitions. Data analyses. California. Ground shaking. Generalized linear mixed models. Goodness-of ...

Longitudinal data modeling is complicated by the necessity to deal appropriately with the correlation between observations made on the same individual. Building on an earlier nonrobust version ...

"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 ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...