Modern measurement techniques allow researchers to gather ever more data in less time. In many cases, however, the primary or raw data have to be further analyzed, be it for the verification of a ...

This is a preview. Log in through your library . Abstract We consider the problem of fitting a generalized linear model to overdispersed data, focussing on a quasilikelihood approach in which the ...

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, ...

The traditional linear transformation model assumes a linear relationship between the transformed response and the covariates. However, in real data, this linear relationship may be violated. We ...