Risk of Error and the Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial VerificationJ. A. Roldán Nofuentes and J. D. Luna Del Castillo Journal of Applied Statistics, 2007, vol. 34, issue 8, pages 887-898 Abstract: The accuracy of a binary diagnostic test is usually measured in terms of its sensitivity and its specificity, or through positive and negative predictive values. Another way to describe the validity of a binary diagnostic test is the risk of error and the kappa coefficient of the risk of error. The risk of error is the average loss that is caused when incorrectly classifying a non-diseased or a diseased patient, and the kappa coefficient of the risk of error is a measure of the agreement between the diagnostic test and the gold standard. In the presence of partial verification of the disease, the disease status of some patients is unknown, and therefore the evaluation of a diagnostic test cannot be carried out through the traditional method. In this paper, we have deduced the maximum likelihood estimators and variances of the risk of error and of the kappa coefficient of the risk of error in the presence of partial verification of the disease. Simulation experiments have been carried out to study the effect of the verification probabilities on the coverage of the confidence interval of the kappa coefficient. Keywords: Covariates; Kappa; partial verification; risk; sensitivity; specificity; verification bias (search for similar items in EconPapers) Downloads: (external link) Related works: Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Applied Statistics is edited by Professor Gopal K. Kanji More articles in Journal of Applied Statistics from Taylor and Francis Journals |
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