Generalized Estimating Equations (GEE) for Mixed Logistic Models

Abstract

In this article, the problem of estimating the fixed effects parameters and the variance components in logistic mixed models is considered. It is well known that estimating these parameters by the method of maximum likelihood faces computational difficulties. As an alternative, we propose the Generalized Estimating Equations approach (denoted, GEE) defined by Liang and Zeger. The estimators obtained are consistent and asymptotically normal. We illustrate this method with simulations and with an analysis of real data in quality of life.

Keywords:

• Generalized linear mixed model
• Logistic model
• Generalized Estimating Equations
• Fisher-scoring algorithm
• Rasch model