Generalized likelihood ratios for quantitative diagnostic test scores
Affiliations
- From the Department of Emergency Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
Correspondence
- Address reprint requests to Dr Tandberg, ACC 4-West, Dept of Emergency Medicine, UNM School of Medicine, Albuquerque, NM 87131-5246.

Affiliations
- From the Department of Emergency Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
Correspondence
- Address reprint requests to Dr Tandberg, ACC 4-West, Dept of Emergency Medicine, UNM School of Medicine, Albuquerque, NM 87131-5246.
Affiliations
- the Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
Affiliations
- the Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
To view the full text, please login as a subscribed user or purchase a subscription. Click here to view the full text on ScienceDirect.
Abstract
The reduction of quantitative diagnostic test scores to the dichotomous case is a wasteful and unnecessary simplification in the era of high-speed computing. Physicians could make better use of the information embedded in quantitative test results if modern generalized curve estimation techniques were applied to the likelihood functions of Bayes' theorem. Hand calculations could be completely avoided and computed graphical summaries provided instead. Graphs showing posttest probability of disease as a function of pretest probability with confidence intervals (POD plots) would enhance acceptance of these techniques if they were immediately available at the computer terminal when test results were retrieved. Such constructs would also provide immediate feedback to physicians when a valueless test had been ordered.
Keywords:
Bayes' theorem, computing, decision theory, diagnosis, Fourier series, Kernel estimation, likelihood, probability, statisticsTo access this article, please choose from the options below
Purchase access to this article
Claim Access
If you are a current subscriber with Society Membership or an Account Number, claim your access now.
Subscribe to this title
Purchase a subscription to gain access to this and all other articles in this journal.
Institutional Access
Visit ScienceDirect to see if you have access via your institution.
Article Tools
Related Articles
Searching for related articles..
