In generalized linear models, the response is assumed to possess a probability distribution of the exponential form. That is, the probability density of the response Y for continuous response ...

This is the GEE equivalent of the inverse of the Fisher information matrix that is often used in generalized linear models as an estimator of the covariance estimate of the maximum likelihood ...

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, ...

This approach eventually leads to a special area of statistics called the generalized linear model (GLM) (McCullagh and Nelder, 1989). Xu and Hu (2010) recently developed a GLM approach to ...

These types of situations can often be modeled well by a large class of regression models called generalized linear models (GLM). We will go over some of the basic statistical concepts of GLM and how ...