Cox’s Model for Prison Partly Interval Censored Data

Abstract

Abstract The term survival analysis has been used in examines and models the time until the events occur. The most common tool for studying the dependency of survival time on predictor variables is Cox model proportional hazards regression model. In this paper we present a simple modification of Cox’s proportional hazards model using the partial likelihood principle technique based on Newton Rapson method. Simulation is conducted based on prison partly interval censored data set with particular sample sizes to evaluate the performance of the proposed model, and it shows that the model is feasible and works well.