The initial conditions problem in longitudinal binary process: A simulation study

Abstract

In this paper we report some simulation studies to compare two basic approaches in modelling the random effects for longitudinal binary data. The first, naive approach, treats the endogenous initial conditions as exogenous and the second, correct approach, models the initial conditions as endogenous. The initial conditions problem in binary data, with unobserved heterogeneity, arises when the process has a Markov property. To see the effect of the error variance and Markov effect, different values for these parameters are considered. We will apply the proposed approach to the data on depression. We show that, in the presence of heterogeneity and stat dependence, ignoring the initial conditions results in biased estimates and misleading interpretation.