Using informative priors for handling missing data problem in Cox regression

被引：0
|
作者：
Alkan, Nesrin [1 ]
Terzi, Yuksel [2 ]
Cengiz, M. Ali [2 ]
机构：
[1] Sinop Univ, Dept Stat, Sinop, Turkey
[2] Ondokuz Mayis Univ, Dept Stat, Samsun, Turkey
来源：
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2017年 / 46卷 / 10期
关键词：
Bayesian Cox regression; Cox regression; Missing at random; Missing value;
D O I：
10.1080/03610918.2016.1248568
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：
The aim of this study is to determine the effect of informative priors for variables with missing value and to compare Bayesian Cox regression and Cox regression analysis. For this purpose, firstly simulated data sets with different sample size within different missing rate were generated and each of data sets were analysed by Cox regression and Bayesian Cox regression with informative prior. Secondly lung cancer data set as real data set was used foranalysis. Consequently, using informative priors for variables with missing value solved the missing data problem.
引用
收藏
页码：7614 / 7623
页数：10
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