Bayesian Analysis

A Bayesian Semiparametric Temporally-Stratified Proportional Hazards Model with Spatial Frailties

Timothy E. Hanson, Alejandro Jara, and Luping Zhao

Full-text: Open access

Abstract

Incorporating temporal and spatial variation could potentially enhance information gathered from survival data. This paper proposes a Bayesian semi-parametric model for capturing spatio-temporal heterogeneity within the proportional hazards framework. The spatial correlation is introduced in the form of county-level frailties. The temporal effect is introduced by considering the stratification of the proportional hazards model, where the time{dependent hazards are indirectly modeled using a probability model for related probability distributions. With this aim, an autoregressive dependent tailfree process is introduced. The full Kullback-Leibler support of the proposed process is provided. The approach is illustrated using simulated data and data from the Surveillance Epidemiology and End Results database of the National Cancer Institute on patients in Iowa diagnosed with breast cancer.

Article information

Source
Bayesian Anal., Volume 7, Number 1 (2012), 147-188.

Dates
First available in Project Euclid: 13 June 2012

Permanent link to this document
https://projecteuclid.org/euclid.ba/1339616728

Digital Object Identifier
doi:10.1214/12-BA705

Mathematical Reviews number (MathSciNet)
MR2896715

Zentralblatt MATH identifier
1330.62368

Keywords
Spatio-temporal modeling Dependent processes Tailfree processes Breast cancer

Citation

Hanson, Timothy E.; Jara, Alejandro; Zhao, Luping. A Bayesian Semiparametric Temporally-Stratified Proportional Hazards Model with Spatial Frailties. Bayesian Anal. 7 (2012), no. 1, 147--188. doi:10.1214/12-BA705. https://projecteuclid.org/euclid.ba/1339616728


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