Suggested diagnostics for influence on the estimated regression coefficients in a generalized linear model have generally approximated the effect of deleting a single case. We apply the local ...

This is a preview. Log in through your library . Abstract The EM algorithm is used to obtain estimators of regression coefficients for generalized linear models with canonical link when normally ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...

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 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 ...

SAS/STAT software contains two procedures for fitting general linear models to panel data. The GLM procedure fits general linear models involving fixed effects. The more general MIXED procedure fits ...