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 …

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 …

Inference for cross-sectional models using longitudinal data, can be accomplished with
generalized estimating equations (Zeger and Liang, 1992). We show that either a diagonal …

Abstract Liang & Zeger (1986) introduced a generalised estimating equations approach
based on a'working'correlation matrix to obtain consistent and efficient estimators of …

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

This paper considers extensions of logistic regression to the case where the binary outcome
variable is observed repeatedly for each subject. We propose two working models that lead …

We consider the multiple regression model E (y)= μ, μ= g (x T β), var (y)—[sgrave] 2 (μ) with
predictors x, link function g, and variance function [sgrave] 2 (·). The aim is to reduce the …

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 …

This paper discusses a quasi-likelihood (QL) approach to regression analysis with time
series data. We consider a class of Markov models, referred to by Cox (1981, Scandinavian …

We consider generalized linear models for regression modeling of count time series. We
give easily verifiable conditions for obtaining weak dependence for such models. These …