Linear mixed model (LMM) methodology is a powerful technology to analyze models containing both the fixed and random effects. The model was first proposed to estimate genetic parameters for unbalanced ...

This paper presents an attempt to explicate some common features of several superficially diverse techniques of data analysis and to indicate how the logic of a single abstract model is relevant to ...

Researchers from many fields can benefit from applied knowledge of general linear models. This class of models includes the t-test (paired and two sample), regression, ANOVA, and ANCOVA. Like all ...

This paper develops a class of models to deal with missing data from longitudinal studies. We assume that separate models for the primary response and missingness (e.g., number of missed visits) are ...

This section provides an overview of a likelihood-based approach to general linear mixed models. This approach simplifies and unifies many common statistical analyses, including those involving ...

This course is available on the BSc in Actuarial Science, BSc in Business Mathematics and Statistics, BSc in Financial Mathematics and Statistics, BSc in Mathematics with Economics and BSc in ...

The GLM procedure fits general linear models to data, and it can perform regression, analysis of variance, analysis of covariance, and many other analyses. The following features for regression ...