Some Observations in Likelihood Based Fitting of Longitudinal Models for Binary Data

Abstract

Different models are used in practice for describing a binary lon- gitudinal data. In this paper we consider the joint probability models, the marginal models, and the combined models for describing such the best. The combined model consists of a joint probability model and a marginal model at two different levels. We present some striking empirical observa- tions on the closeness of the estimates and their standard errors for some parameters of the models considered in describing a from Fitzmaurice and Laird (1993) and consequently giving new insight from this data. We present the in a complete factorial arrangement with 4 factors at 2 levels. We introduce the concept of data representing a model completely and explain data balance as well as chance balance. We also consider the best model selection problem for describing this and use the Search Linear Model concepts known in Fractional Factorial Design research (Sri- vastava (1975)).