Modelling stochastic order in the analysis of receiver operating characteristic data: Bayesian non‐parametric approaches

Timothy E. Hanson, Athanasios Kottas and Adam J. Branscum

Journal of the Royal Statistical Society Series C, 2008, vol. 57, issue 2, 207-225

Abstract: Summary. The evaluation of the performance of a continuous diagnostic measure is a commonly encountered task in medical research. We develop Bayesian non‐parametric models that use Dirichlet process mixtures and mixtures of Polya trees for the analysis of continuous serologic data. The modelling approach differs from traditional approaches to the analysis of receiver operating characteristic curve data in that it incorporates a stochastic ordering constraint for the distributions of serologic values for the infected and non‐infected populations. Biologically such a constraint is virtually always feasible because serologic values from infected individuals tend to be higher than those for non‐infected individuals. The models proposed provide data‐driven inferences for the infected and non‐infected population distributions, and for the receiver operating characteristic curve and corresponding area under the curve. We illustrate and compare the predictive performance of the Dirichlet process mixture and mixture of Polya trees approaches by using serologic data for Johne's disease in dairy cattle.

Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9876.2007.00609.x

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:57:y:2008:i:2:p:207-225

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().