Abstract:
The classical Cox model is the most popular procedure for studying right-censored data
in survival analysis. However, it is based on the fundamental assumption of proportional hazards
(PH). Modified Cox models, stratified and extended, have been widely employed as solutions when
the PH assumption is violated. Nevertheless, prior comparisons of the modified Cox models did
not employ comprehensive Monte-Carlo simulations to carry out a comparative analysis between
the two models. In this paper, we conducted extensive Monte-Carlo simulation to compare the
performance of the stratified and extended Cox models under varying censoring rates, sample sizes,
and survival distributions. Our results suggest that the models’ performance at varying censoring
rates and sample sizes is robust to the distribution of survival times. Thus, their performance under
Weibull survival times was comparable to that of exponential survival times. Furthermore, we found
that the extended Cox model outperformed other models under every combination of censoring,
sample size and survival distribution.
