Estimation of the Average Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification

José Antonio Roldán-Nofuentes and Saad Bouh Regad
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José Antonio Roldán-Nofuentes: Department of Statistics, School of Medicine, University of Granada, 18016 Granada, Spain
Saad Bouh Regad: Epidemiology and Public Health Research Unit and URMCD, School of Medicine, University of Nouakchott Alaasriya, Nouakchott BP 880, Mauritania

Mathematics, 2021, vol. 9, issue 14, 1-17

Abstract: The average kappa coefficient of a binary diagnostic test is a measure of the beyond-chance average agreement between the binary diagnostic test and the gold standard, and it depends on the sensitivity and specificity of the diagnostic test and on disease prevalence. In this manuscript the estimation of the average kappa coefficient of a diagnostic test in the presence of verification bias is studied. Confidence intervals for the average kappa coefficient are studied applying the methods of maximum likelihood and multiple imputation by chained equations. Simulation experiments have been carried out to study the asymptotic behaviors of the proposed intervals, given some application rules. The results obtained in our simulation experiments have shown that the multiple imputation by chained equations method provides better results than the maximum likelihood method. A function has been written in R to estimate the average kappa coefficient by applying multiple imputation. The results have been applied to the diagnosis of liver disease.

Keywords: average kappa coefficient; missing data; multiple imputation by chained equations; partial verification (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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