Empirical likelihood-based confidence intervals for the sensitivity of a continuous-scale diagnostic test at a fixed level of specificity.
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.
Gengsheng Qin
Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia 30302-4110, USA. gqin@gsu.edu
Davis
Angela E
AE
Jing
Bing-Yi
BY
D019540:Area Under Curve; D018395:CA-19-9 Antigen / Q000097:blood; D016009:Chi-Square Distribution; D016001:Confidence Intervals; D003955:Diagnostic Tests, Routine / Q000706:statistics & numerical data*; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D010190:Pancreatic Neoplasms / Q000097:blood / Q000175:diagnosis; D012680:Sensitivity and Specificity
D018395:CA-19-9 Antigen