Flexible regression models for ROC and risk analysis, with or without a gold standard

Author:

Branscum Adam J.1,Johnson Wesley O.2,Hanson Timothy E.3,Baron Andre T.4

Affiliation:

1. Biostatistics Program; Oregon State University; Corvallis 97331 Oregon U.S.A.

2. Department of Statistics; University of California; Irvine CA U.S.A.

3. Department of Statistics; University of South Carolina; Columbia SC U.S.A.

4. Loring Life Sciences, Inc.; Lexington KY U.S.A.

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Reference64 articles.

1. Bayesian semi-parametric ROC analysis;Erkanli;Statistics in Medicine,2006

2. Nonparametric estimation of ROC curves based on Bayesian models when the true disease state is unknown;Wang;Journal of Agricultural, Biological, and Environmental Statistics,2007

3. Development of a method for Bayesian nonparametric ROC analysis with application to an ELISA for Johne's disease in dairy cattle;Fosgate;Preventive Veterinary Medicine,2007

4. Bayesian semiparametric ROC curve estimation and disease diagnosis;Branscum;Statistics in Medicine,2008

5. Modelling stochastic order in the analysis of ROC data: Bayesian non-parametric approaches;Hanson;Applied Statistics,2008

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