Statistical methodological review for time-to-event data

被引:4
|
作者
Rahardja, Dewi [1 ]
Wu, Han [2 ]
机构
[1] US Dept Def, Ft George G Meade, MD 20755 USA
[2] Minnesota State Univ, Dept Math & Stat, Mankato, MN 56001 USA
来源
JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS | 2018年 / 21卷 / 01期
关键词
Kaplan-Meier (K-M); Product Limit Estimator; Life Table; Log-Rank test; Cox model; proportional hazard model; Time-To-Event Data Analysis; Survival/Failure Analysis; Reliability Analysis; Censoring;
D O I
10.1080/09720510.2017.1411029
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
For Time-To-Event (TTE) data, various statistical methods have been discussed in the literature. In this article we give a review of the TTE data analysis methods. The review includes descriptive methods, such as Kaplan-Meier estimator and Life Table, as well as inferential methods, such as the Log-Rank test and the Cox (Proportional Hazard) model. We provide a roadmap in a figure or diagram format to which methods are practically available to use in the literature. In addition, the implementation of these methods in popular statistical software packages such as SAS is also presented. This article will be very helpful for practitioners, investigators, and researchers to determine which TTE data analysis method (along with the corresponding SAS code) are available to use in various fields of study such as clinical trials, epidemiology, etc., both for the design phase of a study in prospective study or retrospective study analysis.
引用
收藏
页数:12
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