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Erschienen in: Lifetime Data Analysis 3/2017

18.03.2016

Generalized accelerated failure time spatial frailty model for arbitrarily censored data

verfasst von: Haiming Zhou, Timothy Hanson, Jiajia Zhang

Erschienen in: Lifetime Data Analysis | Ausgabe 3/2017

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Abstract

Flexible incorporation of both geographical patterning and risk effects in cancer survival models is becoming increasingly important, due in part to the recent availability of large cancer registries. Most spatial survival models stochastically order survival curves from different subpopulations. However, it is common for survival curves from two subpopulations to cross in epidemiological cancer studies and thus interpretable standard survival models can not be used without some modification. Common fixes are the inclusion of time-varying regression effects in the proportional hazards model or fully nonparametric modeling, either of which destroys any easy interpretability from the fitted model. To address this issue, we develop a generalized accelerated failure time model which allows stratification on continuous or categorical covariates, as well as providing per-variable tests for whether stratification is necessary via novel approximate Bayes factors. The model is interpretable in terms of how median survival changes and is able to capture crossing survival curves in the presence of spatial correlation. A detailed Markov chain Monte Carlo algorithm is presented for posterior inference and a freely available function frailtyGAFT is provided to fit the model in the R package spBayesSurv. We apply our approach to a subset of the prostate cancer data gathered for Louisiana by the surveillance, epidemiology, and end results program of the National Cancer Institute.

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Metadaten
Titel
Generalized accelerated failure time spatial frailty model for arbitrarily censored data
verfasst von
Haiming Zhou
Timothy Hanson
Jiajia Zhang
Publikationsdatum
18.03.2016
Verlag
Springer US
Erschienen in
Lifetime Data Analysis / Ausgabe 3/2017
Print ISSN: 1380-7870
Elektronische ISSN: 1572-9249
DOI
https://doi.org/10.1007/s10985-016-9361-4

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