A simulation/case study under the use of robust Poisson and log-binomial model with generalized estimating equation models regarding non-independent data / 中华流行病学杂志

ABSTRACT

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.