Marginal model is one of the approaches that can be used in analyzing longitudinal data. In this model, to obtain valid inference, correlations between responses of the same individuals are considered as parameters to be estimated. The various marginal models for analyzing longitudinal data with binary responses such as marginal models with marginal odds ratio, conditional odds ratio, dependence ratio, multivariate probit and the method of generalized estimating equations (GEE) are reviewed and compared. Some residuals for examining the goodness of fit of these models are presented. In an empirical example, these models are fitted to some data.