Medical Decision Making

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Click here to browse AJSM online!

Sign In to gain access to subscriptions and/or personal tools.
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Walsh, S. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Walsh, S. J.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
Medical Decision Making, Vol. 19, No. 2, 193-201 (1999)
DOI: 10.1177/0272989X9901900210


Notes

Goodness-of-fit Issues in ROC Curve Estimation

Stephen J. Walsh

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)


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
CirculationHome page
K. H. Zou, A. J. O'Malley, and L. Mauri
Receiver-Operating Characteristic Analysis for Evaluating Diagnostic Tests and Predictive Models
Circulation, February 6, 2007; 115(5): 654 - 657.
[Full Text] [PDF]


Home page
Med Decis MakingHome page
M. Douglas
Plotting ROC Curves: Giving Us Fits
Med Decis Making, April 1, 1999; 19(2): 214 - 215.
[PDF]