REGRESSION-MODELS FOR LONGITUDINAL BINARY RESPONSES WITH INFORMATIVE DROP-OUTS

Abstract

This paper reviews both likelihood-based and non-likelihood (generalized estimating equations) regression models for longitudinal binary responses when there are drop-outs. Throughout, it is assumed that the regression parameters for the marginal expectations of the binary responses are of primary scientific interest. The association or time dependence between the responses is largely regarded as a nuisance characteristic of the data. The performance of the methods is compared, in terms of asymptotic bias, under misspecification of the association between the responses and the missing data mechanism or drop-out process.