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 ...

The GLM procedure is the flagship tool for analysis of variance in SAS/STAT software. It performs analysis of variance by using least squares regression to fit general linear models, as described in ...

Generally speaking, there are two types of outcomes (i.e. response) in statistical analysis: continuous and categorical responses. Linear Models (LM) are one of the most commonly used statistical ...

We consider the problem of experimental design when the response is modeled by a generalized linear model (GLM) and the experimental plan can be determined sequentially. Most previous research on this ...

An analysis-of-variance model can be written as a linear model, which is an equation that predicts the response as a linear function of parameters and design variables. In general, A one-way model is ...

Although generalized linear models (GLM's) are an attractive and widely used class of models, they are limited in the range of density shapes that they can provide. For instance, they are unimodal ...