Semiparametric Bayesian Survival Analysis using Models with Log-linear Median
Article first published online: 26 SEP 2012
© 2012, The International Biometric Society No claim to original US government works
Volume 68, Issue 4, pages 1136–1145, December 2012
How to Cite
Lin, J., Sinha, D., Lipsitz, S. and Polpo, A. (2012), Semiparametric Bayesian Survival Analysis using Models with Log-linear Median. Biometrics, 68: 1136–1145. doi: 10.1111/j.1541-0420.2012.01782.x
- Issue published online: 21 DEC 2012
- Article first published online: 26 SEP 2012
- Received April 2011. Revised March 2012. Accepted March 2012.
- Bayesian Survival analysis;
- Log-linear median regression;
- Quantile regression;
Summary We present a novel semiparametric survival model with a log-linear median regression function. As a useful alternative to existing semiparametric models, our large model class has many important practical advantages, including interpretation of the regression parameters via the median and the ability to address heteroscedasticity. We demonstrate that our modeling technique facilitates the ease of prior elicitation and computation for both parametric and semiparametric Bayesian analysis of survival data. We illustrate the advantages of our modeling, as well as model diagnostics, via a reanalysis of a small-cell lung cancer study. Results of our simulation study provide further support for our model in practice.