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Empirical likelihood-based confidence intervals for the sensitivity of a continuous-scale diagnostic test at a fixed level of specificity

¹ Department of Mathematics and Statistics, Georgia State University, P.O. Box 4110, Atlanta, GA 30302-4110, USA
² Georgia State University, Atlanta, Georgia, USA
³ Hong Kong University of Science and Technology, Hong Kong

^* To whom correspondence should be addressed. E-mail: matgjq{at}langate.gsu.edu.

	Abstract

For a continuous-scale diagnostic test, it is often of interest to find the range of the sensitivity of the test at the cut-off that yields a desired specificity. In this article, we first define a profile empirical likelihood ratio for the sensitivity of a continuous-scale diagnostic test and show that its limiting distribution is a scaled chi-square distribution. We then propose two new empirical likelihood-based confidence intervals for the sensitivity of the test at a fixed level of specificity by using the scaled chi-square distribution. Simulation studies are conducted to compare the finite sample performance of the newly proposed intervals with the existing intervals for the sensitivity in terms of coverage probability. A real example is used to illustrate the application of the recommended methods.

First published on August 4, 2009
Statistical Methods in Medical Research 2009, doi:10.1177/0962280209105512


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