CoxPhLb: An R Package for Analyzing Length Biased Data under Cox Model

被引:0
|
作者
Lee, Chi Hyun [1 ]
Zhou, Heng [2 ]
Ning, Jing [3 ]
Liu, Diane D. [3 ]
Shen, Yu [3 ]
机构
[1] Univ Massachusetts, Dept Biostat & Epidemiol, Amherst, MA 01003 USA
[2] Merck & Co Inc, Biostat Hutt Res Decis Sci, Kenilworth, NJ USA
[3] Univ Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX USA
来源
R JOURNAL | 2020年 / 12卷 / 01期
基金
美国国家卫生研究院;
关键词
PREVALENT COHORT; STATIONARITY; LIKELIHOOD; CHECKING; DURATION;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Data subject to length-biased sampling are frequently encountered in various applications including prevalent cohort studies and are considered as a special case of left-truncated data under the stationarity assumption. Many semiparametric regression methods have been proposed for length-biased data to model the association between covariates and the survival outcome of interest. In this paper, we present a brief review of the statistical methodologies established for the analysis of length-biased data under the Cox model, which is the most commonly adopted semiparametric model, and introduce an R package CoxPhLb that implements these methods. Specifically, the package includes features such as fitting the Cox model to explore covariate effects on survival times and checking the proportional hazards model assumptions and the stationarity assumption. We illustrate usage of the package with a simulated data example and a real dataset, the Channing House data, which are publicly available.
引用
收藏
页码:118 / 130
页数:13
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