Bias in gee estimates from misspecified models for longitudinal data

Consider the use of Generalized Estimating Equations (GEE s ) for estimation of regression parameters from longitudinal series. Let Y it be the outcome for the i th series at time t and let X i = (X i1 ,...,X ini )′ be covariate vectors associated with n i observation times. We investigate bias of GEE estimates for population-average (PA) and conditional parameters under model mis-specification which takes the form of omission of past history from the model for Y it |X i .We provide exact bias results for the identity link, a bias approximation for nonlinear links and simulation results. Bias for either parameter can be positive or negative and depends on the size of the series and the strength of association between observations at times t and t - 1.