A Goodness-of-Fit Test for GEE Models with Binary Longitudinal Data Based on Smoothing Methods

The logistic regression models have received widespread use for analyzing binary response data. In longitudinal studies, correlated data arise and such data are often analyzed by generalized estimating equations (GEE) method. This article proposes an alternative goodness-of-fit test based on nonparametric smoothing approach for assessing the adequacy of GEE fitted models, which can be regarded as an extension of the goodness-of-fit test of le Cessie and van Houwelingen (1991). The approximate expectation and variance of the proposed test statistic are derived. The power performance of test is discussed by simulation study and the testing procedure is illustrated by a clinical trial example.