Abstract: Analysis of data with repeated measures is often accomplished through the use of Generalized Estimating Equations (GEE) methodology. Although methods exist for assessing the adequacy of the fitted models for uncorrelated data with likelihood methods, it is not appropriate to use these methods for models fitted with GEE methodology. Barnhart and Williamson[1] proposed model-based and robust (empirically corrected) goodness-of-fit tests for GEE modeling with binary responses based on partitioning the space of covariates into distinct regions and forming score statistics that are asymptotically distributed as chi-square random variables with the appropriate degrees of freedom. In their suggested GEE approach the correlation between two responses was not considered. We here proposed an alternative procedure based on GEE where the correlation between two responses was considered. We extended their work using different correlation structures exchangeable, autoregressive and pairwise correlation along with their suggested identity correlation structure.