A Bayesian hierarchical modeling approach for studying the factors affecting the stage at diagnosis of prostate cancer
We extend the baseline‐category logits model for categorical response data to
accommodate two distinct kinds of clustering. Our extension introduces random effects that …
accommodate two distinct kinds of clustering. Our extension introduces random effects that …
A Bayesian hierarchical modeling approach for studying the factors affecting the stage at diagnosis of prostate cancer
H Zhou, AB Lawson, JR Hebert… - Statistics in …, 2008 - pubmed.ncbi.nlm.nih.gov
We extend the baseline-category logits model for categorical response data to
accommodate two distinct kinds of clustering. Our extension introduces random effects that …
accommodate two distinct kinds of clustering. Our extension introduces random effects that …
[引用][C] A Bayesian hierarchical modeling approach for studying the factors affecting the stage at diagnosis of prostate cancer
H Zhou, AB Lawson, JR Hébert… - Statistics in …, 2008 - scholarcommons.sc.edu
"A Bayesian hierarchical modeling approach for studying the factors aff" by Huafeng Zhou,
Andrew B. Lawson et al. Home Search Browse Collections My Account About DC Network …
Andrew B. Lawson et al. Home Search Browse Collections My Account About DC Network …
A Bayesian hierarchical modeling approach for studying the factors affecting the stage at diagnosis of prostate cancer.
H Zhou, AB Lawson, JR Hebert, EH Slate… - Statistics in …, 2008 - europepmc.org
We extend the baseline-category logits model for categorical response data to
accommodate two distinct kinds of clustering. Our extension introduces random effects that …
accommodate two distinct kinds of clustering. Our extension introduces random effects that …