A Bayesian hierarchical modeling approach for studying the factors affecting the stage at diagnosis of prostate cancer

Author(s)

Huafeng Zhou, University of South Carolina - Columbia
Andrew B. Lawson, University of South Carolina - Columbia
James R. Hébert, University of South Carolina - ColumbiaFollow
Elizabeth H. Slate, University of South Carolina - Columbia
Elizabeth G. Hill, University of South Carolina - Columbia

Document Type

Article

Publication Info

Statistics in Medicine, Volume 27, Issue 9, 2008, pages 1468-1489.

Zhou, H., Lawson, A. B., Hebert, J. R., Slate, E. H. & Hill, E. G. (2008). A Bayesian hierarchical modeling approach for studying the factors affecting the stage at diagnosis of prostate cancer. Statistics in Medicine, 27(9), 1468-1489. DOI: 10.1002/sim.3024

© 2007 John Wiley & Sons, Ltd.

Rights

Zhou, H., Lawson, A. B., Hebert, J. R., Slate, E. H. & Hill, E. G. (2008). A Bayesian hierarchical modeling approach for studying the factors affecting the stage at diagnosis of prostate cancer. Statistics in Medicine, 27(9), 1468-1489. DOI: 10.1002/sim.3024

© 2007 John Wiley & Sons, Ltd.