This article discusses extensions of generalized linear models for the analysis of
longitudinal data. Two approaches are considered: subject-specific (SS) models in which …

Longitudinal data sets are comprised of repeated observations of an outcome and a set of
covariates for each of many subjects. One objective of statistical analysis is to describe the …

This paper proposes an extension of generalized linear models to the analysis of
longitudinal data. We introduce a class of estimating equations that give consistent …

It is common to observe a vector of discrete and/or continuous responses in scientific
problems where the objective is to characterize the dependence of each response on …

The method of generalized estimating equations (GEE) is often used to analyze longitudinal
and other correlated response data, particularly if responses are binary. However, few …

Applying Generalized Linear Models describes how generalized linear modelling
procedures can be used for statistical modelling in many different fields, without becoming …

Liang and Zeger proposed an extension of generalized linear models to the analysis of
longitudinal data. Their approach is closely related to quasi‐likelihood methods and can …

In this paper, we review analytic methods for regression models for longitudinal categorical
responses. We focus on both likelihood-based approaches and non-likelihood approaches …

Do you have data that is not normally distributed and don′ t know how to analyze it using
generalized linear models (GLM)? Beginning with a discussion of fundamental statistical …

We explore a class of regression and generalized regression models in which the
coefficients are allowed to vary as smooth functions of other variables. General algorithms …