Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 1 3/4 2015 10 19 100 104 EN Habibollah Esmaily Department of Biostatistics, Health Sciences Research Center Mashhad University of Medical Sciences, Mashhad, Khorasan Razavi, Iran Fatemeh Salmani Department of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran MohammadReza Meshkani Department of Statistics, School of Mathematics Sciences, Shahid Beheshti University, Tehran, Iran Anoushirvan Kazemnejad Department of Biostatistics, Medical Sciences, Tarbiat Modares University, Tehran, Iran NasserReza Arghami Department of Statistics, School of Mathematics sciences, Ferdowsi University, Mashhad, Khorasan Razavi, Iran 2015 10 13 2015 10 13 Longitudinal  study  plays  an  important  role  in  the  epidemiological,  clinical, and  social  science studies. In these kinds of studies, every individual is observed frequently during a period of time. The statistical analysis of longitudinal presents special opportunities  and challenges. The repeated outcomes for one individual tend to be correlated among themselves also one of the problems that we face in longitudinal studies is the missing data. These two issues are taken into account in this article. By using the logit link function, designed for longitudinal data, we introduce a mixed model, and then present the evaluation of variance components by Bayesian methods. The applied method exploits the non-conjugate priors. The conjugate priors, however, are easier to deal with. Finally, an application of the model in a clinical experiment is presented. https://jbe.tums.ac.ir/index.php/jbe/article/view/5 https://jbe.tums.ac.ir/index.php/jbe/article/download/5/29