Using informative priors for handling missing data problem in Cox regression
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Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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.
Açıklama
Anahtar Kelimeler
Bayesian Cox regression, Cox regression, Missing at random, Missing value
Kaynak
Communications in Statistics-Simulation and Computation
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
46
Sayı
10
