Comparing Marginal and Transition Models In The Analysis of Binary Longitudinal Data: a Simulation Study

Longitudinal studies widely used in many branches of science، especial-lly medical science. In the past two deca-des، many models have been proposed for the evaluation of such data. These models are also developed to investigate various re-sponse variables such that categorical varia-bles that have many applications in medical research. While many papers have comp-ared the marginal and random effects mo-dels but fewer studies have compared the marginal and transition models. This paper used simulation with different scenarios for corr-elation، sample size and repeated measures and calculated ROC Curve for two models. Then estimated AUC for them and comp-arison was performed. If intensity transition for healthy to disease was large and patient remained disease for a long time that is better used transition model to prediction. In addition، in conditions that intensity transition in any status was equal or trends of transition inte-nsity was inverse of position1 that healthy people remained health for a long time and patients recovered quickly، that is better used marginal model. Discussion & In analysis of longitudinal data for achieving more accur-ate results when purpose of study was pred-iction، that is better intensity transition bet-ween status was considered and then dec-ided which model is choosen.