A Bayesian hierarchical mixture model for platelet-derived growth factor receptor phosphorylation to improve estimation of progression-free survival in prostate cancer-Reference-Cited by-同舟云学术

A Bayesian hierarchical mixture model for platelet-derived growth factor receptor phosphorylation to improve estimation of progression-free survival in prostate cancer

Published:2010-01 Issue:1 Volume:59 Page:19-34
ISSN:0035-9254
Container-title:Journal of the Royal Statistical Society: Series C (Applied Statistics)
language:en
Short-container-title:

Author:

Morita Satoshi,Thall Peter F.,Bekele B. Nebiyou,Mathew Paul

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1467-9876.2009.00680.x/fullpdf

Reference9 articles.

1. Gilks, W. R., Richardson, S. and Spiegelhalter, D. J. (eds) (1996) Markov Chain Monte Carlo in Practice. London: Chapman and Hall.

2. Bayesian Survival Analysis

3. Platelet-derived growth factor receptor inhibition and chemotherapy for castration-resistant prostate cancer with bone metastases;Mathew;Clin. Cancer Res.,2007

4. Finite Mixture Models

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