Résumé
To explore the appropriate method in estimating relative risk (RR)/prevalence ratio (PR) related to non-independent datasets.The simulation datasets generated by computer and case study were analyzed by two generalized estimating equation (GEE) models to investigate and compare the related applicability.Both convergence effects of log-binomial-GEE model and Robust Poisson-GEE model were almost 100%.The estimation results of the two GEE models were both closer to the true value.95%CI coverage of the two GEE models increased along with the reduction of class aggregation or the increase of the number of categories.Robust-Poisson-GEE model seemed to be more stable and steady than the log-binomial-GEE.The two GEE models could correctly evaluate the effects of exposure on the outcome in the case study.Rarely,there appeared problems on convergence of Robust Poisson or log-binomial-GEE model,and the accuracy was high.Both models could be used to estimate the RR/PR on non-independent epidemiological data.