Bayes Analysis of mRS Followup Data in the Presence of Multiple Categories

Abstract

Situations are often encountered, especially in medical sciences, where observing each stage of an event is necessary and overlooking it might be risky for the wellbeing of an individual. Keeping the same very viewpoint, this article presents the analysis of a real Modified Rankin score data with multiple responses from a Bayesian perspective using polytomous logistic regression model. The study involves utilizing the Markov Chain Monte Carlo technique for acquiring samples from the resulting posterior distribution. Finally, to check the scope of the model simplification, several covariates have been tested against zero and then a comparison between the full model and the simplified model has been proposed based on deviance information criterion.