Generalized linear models (GLMs), as defined by J. A. Nelder and R. W. M. Wedderburn (1972), unify a class of regression models for categorical, discrete, and continuous response variables. As an ...

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, ...

Dalei Yu, Xinyu Zhang, Kelvin K.W. Yau, Asymptotic properties and information criteria for misspecified generalized linear mixed models, Journal of the Royal Statistical Society.

Generalized Linear Models Generalized Linear Models Course Topics Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, ...

A generalized linear model extends the traditional linear model and is, therefore, applicable to a wider range of data analysis problems. A generalized linear model consists of the following ...

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 ...