Using informative priors for handling missing data problem in Cox regression

Alkan, Nesrin; Terzi, Yüksel; Cengiz, Mehmet

doi:10.1080/03610918.2016.1248568

Using informative priors for handling missing data problem in Cox regression

Alkan N., Terzi Y., Cengiz M. A.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.46, sa.10, ss.7614-7623, 2017 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 46 Sayı: 10
Basım Tarihi: 2017
Doi Numarası: 10.1080/03610918.2016.1248568
Dergi Adı: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Sayfa Sayıları: ss.7614-7623
Anahtar Kelimeler: Bayesian Cox regression, Cox regression, Missing at random, Missing value
Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
Ondokuz Mayıs Üniversitesi Adresli: Evet

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.