Discussion on Methods for Tied Survival Times in Cox Model
10.11842/wst.2017.09.007
- VernacularTitle:运用Cox模型时打结数据的处理方法探讨
- Author:
Wenli ZHANG
1
;
Tong ZHANG
;
Danhui YI
;
Yufei YANG
Author Information
1. 中国人民大学应用统计科学研究中心
- Keywords:
Survival analysis;
Cox model;
tied data;
partial likelihood function
- From:
World Science and Technology-Modernization of Traditional Chinese Medicine
2017;19(9):1449-1454
- CountryChina
- Language:Chinese
-
Abstract:
Cox regression model is one of the most widely used methods in the survival analysis.One assumption of this model is that there is no tie in the failure times,that is,individual has different failure times.In practical applications,the existence of ties in time data is very common.In this paper,four common methods of dealing with ties in Cox model,including Exact method,discrete model method,Efron method and Breslow method,were compared with simulation.The results showed that Exact method and discrete model were the best,but they took the longest time.Efron method and Breslow method were faster but there was a greater deviation in parameter estimation.Moreover,the sample amount and ties degree also affect the results.In general,when there are a few ties,the difference between four methods was small;and in the case of large datasets or a large number of ties,the bias of three approximation methods increased except Exact method.However,there was no significant change on computational time.While the computational time of the Exact method increased rapidly.Therefore,if the estimation precision is not as important as the estimation time,Efron method and Breslow method will be good choices.Efron method is more preferably as it is more precise.And Breslow method tends to underestimate the true β.If there is no limit in time,Exact method and discrete model can be chosen to achieve more accurate results.
