Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 2 1 2016 06 06 40 46 EN Malihe Rezaei Department of Biostatistics, School of Health, Kerman University of Medical Sciences, Kerman, Iran. Ali Akbar Haghdoost Department of Epidemiology, Research enter for Modeling in Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran. Maryam Okhovati Department of Library and Information Science, Medical Informatics Research enter, Kerman University of Medical Sciences, Kerman, Iran. Farzane Zolala Department of Epidemiology, Research Center for Modeling in Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran. Mohammad Reza Baneshi Department of Biostatistics, Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran. 2016 06 06 2016 06 06 Each semester, students are asked to evaluate the academic staff through an online questionnaire. Generalized estimating equations model (GEE), taking into account the correlation between scores, is the established tool to analyze longitudinal data. The aim of this manuscript is to identify characteristics that influence staff score and to address the importance of selection of appropriate correlation structure. We analyzed scores of 336 staff in six consecutive semesters applying GEE with three correlation structures: exchangeable, autoregressive, and unstructured. We also compared the performance of these correlation structures via simulation study. Three normally distributed outcomes with exchangeable correlation structure were simulated. Four independent variables (two continuous and two binary) of which only one was related to the outcome were generated. In the empirical data set, time and academic degree were positively correlated with staffs’ score. Our simulation study showed that the probability that autoregressive and unstructured correlation structures select wrong predictors as being significant is 1.3% and 3.7%. We concluded tha evaluation of staff by students improved the quality of education. In addition, selection of inappropriate correlation structure affects the significance of variables. https://jbe.tums.ac.ir/index.php/jbe/article/view/49 https://jbe.tums.ac.ir/index.php/jbe/article/download/49/39