Jackknife empirical likelihood confidence regions for the evaluation of
continuous-scale diagnostic test with nonignorable verification bias
 
   Lead Investigator:    Haiqi Wang
   Institution      :    Georgia State University
   E-Mail           :    hwang41@student.gsu.edu
   Proposal ID      :    668



   Proposal Description:
   Our goal is to evaluate the diagnostic accuracy of the mini mental state examination test in detecting AD by using jackknife empirical likelihood. We develop some methods to estimate ROC curve under missing not at random. We want to get the performance of those methods by using the real data. ??In a continuous-scale diagnostic test, when a cut-off level is given, the performance of the test in distinguishing diseased subjects from non-diseased subjects can be evaluated by its sensitivity and specificity. Joint inferences for sensitivity and specificity as well as cut-off level play an important role in the assessment of the diagnostic accuracy of the test. Recently we propose various bias-corrected empirical likelihood confidence region for sensitivity and specificity under non-ignoble verification bias, we want to use NACC data ??to examine the performance of our method.