NONPARAMETRIC BAYESIAN-APPROACH TO HAZARD REGRESSION - A CASE-STUDY WITH A LARGE NUMBER OF MISSING COVARIATE VALUES

Authors
ARJAS E LIU LP
Citation
E. Arjas et Lp. Liu, NONPARAMETRIC BAYESIAN-APPROACH TO HAZARD REGRESSION - A CASE-STUDY WITH A LARGE NUMBER OF MISSING COVARIATE VALUES, Statistics in medicine, 15(16), 1996, pp. 1757-1770
Citations number
11
Categorie Soggetti
Statistic & Probability","Medicine, Research & Experimental","Public, Environmental & Occupation Heath","Statistic & Probability","Medical Informatics
Journal title
Statistics in medicine → ACNP
ISSN journal
02776715
Volume
15
Issue
16
Year of publication
1996
Pages
1757 - 1770
Database
ISI
SICI code
0277-6715(1996)15:16<1757:NBTHR->2.0.ZU;2-I
Abstract
A 'packaged' non-parametric multiplicative hazard regression model is proposed, and applied to a study of the effects of some genetic and vi ral factors in the development of spontaneous leukaemia in mice. Hiera rchical modelling and data augmentation are used to deal with the larg e number of missing covariate values. A Bayesian procedure is adopted, and the Metropolis-Hastings algorithm is used in the numerical comput ation of the posterior distribution.