Goodness-of-fit Issues in ROC Curve Estimation

Stephen J. Walsh

Medical Decision Making, 1999, vol. 19, issue 2, 193-201

Abstract: Zhou recently considered goodness-of-fit (GOF) testing for receiver operating char acteristic (ROC) curves estimated by applying the binormal and other bidistributional models to rating method data. He interpreted significant GOF tests as evidence that different decision thresholds were applied to diseased and nondiseased subjects and concluded that, in such circumstances, an ROC curve does not exist. In this article the author demonstrates that the GOF test accommodates many alternative hypoth eses and that a significant test result need not be equated with an interaction between disease status and decision criteria or with non-existence of an ROC curve. He de velops a new family of ROC curves based on a fully parameterized bidistributional model. The family includes the binormal ROC curve, but generalizes its structure by signifying all identifiable deviations in parameters of the latent distributions that define the model. The family provides a unified framework of alternative models to the binor mal assumption and of alternative hypotheses to the GOF test for that assumption. Key words: goodness-of-fit testing; ROC curves; rating method. (Med Decis Making 1999;19:193-201)

Date: 1999
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X9901900210 (text/html)

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:sae:medema:v:19:y:1999:i:2:p:193-201

DOI: 10.1177/0272989X9901900210

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().