Bias in estimating association parameters for longitudinal binary responses with drop-outs

This paper considers the impact of bias in the estimation of the associatio n parameters for longitudinal binary responses when there are drop-outs. A number of different estimating equation approaches are considered for the c ase where drop-out cannot be assumed to be a completely random process. In particular, standard generalized estimating equations (GEE), GEE based on c onditional residuals, GEE based on multivariate normal estimating equations for the covariance matrix, and second-order estimating equations (GEE2) ar e examined. These different GEE estimators are compared in terms of finite sample and asymptotic bias under a variety of drop-out processes. Finally, the relationship between bias in the estimation of the association paramete rs and bias in the estimation of the mean parameters is explored.