Methods for longitudinal binary data with missing observations

Missingness is a common feature of longitudinal studies. In recent years there has been considerable research devoted to the development of methods for the analysis of incomplete longitudinal data. One common practice is imputation by the " last observation carried forward" (LOCF) approach, in which values for missing responses are imputed using observations from the most recently completed assessment. In this talk I will first examine the performance of the LOCF approach where the generalized estimating equations (GEE) are employed as the inferential procedures.