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The analysis of survival data with a non‐susceptible fraction and dual censoring mechanisms
Author(s) -
Gag David R.,
Glickman Mark E.,
Myers Richard H.,
Cupples L. Adrienne
Publication year - 2003
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.1568
Subject(s) - censoring (clinical trials) , disease , age of onset , bayesian probability , markov chain monte carlo , population , survival analysis , markov chain , parametric statistics , medicine , statistics , demography , econometrics , mathematics , environmental health , sociology
It is known that the ages of onset of many diseases are determined by both a genetic predisposition to disease as well as environmental risk factors that are capable of either triggering or hastening the onset of disease. Difficulties in modelling onset ages arise when a large fraction fail to inherit the disease‐causing gene, and multiple reasons for censoring result in unobserved onset ages. We present a parametric Bayesian model that includes subjects with missing age information, non‐susceptible subjects and allows for regression on risk factor information. The model is fit using Markov chain Monte Carlo simulation from the posterior distribution, and allows the simultaneous estimation of the proportion of the population at risk of disease, the mean onset age of disease, survival after disease onset, and the association of risk factors with susceptibility, onset age and survival after onset. An example employing Huntington's disease data is presented. Copyright © 2003 John Wiley & Sons, Ltd.