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Smooth estimation of survival functions and hazard ratios from interval‐censored data using Bayesian penalized B‐splines
Author(s) -
Çetinyürek Yavuz Aysun,
Lambert Philippe
Publication year - 2010
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4081
Subject(s) - covariate , frequentist inference , bayesian probability , hazard ratio , statistics , estimator , censoring (clinical trials) , confidence interval , bayes' theorem , econometrics , hazard , proportional hazards model , mathematics , computer science , bayesian inference , chemistry , organic chemistry
Abstract We discuss the use of Bayesian P‐spline and of the composite link model to estimate survival functions and hazard ratios from interval‐censored data. If one further assumes proportionality of the hazards, the proposed strategy provides a smoothed estimate of the baseline hazard along with estimates of global covariate effects. The frequentist properties of our Bayesian estimators are assessed by an extensive simulation study. We further illustrate the methodology by two examples showing that the proportionality of the hazards might also be found inappropriate from interval‐censored data. Copyright © 2010 John Wiley & Sons, Ltd.