Estimation of the Average Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification Roldán Nofuentes, José Antonio Bouh Regad, Saad Average kappa coefficient Missing data Multiple imputation by chained equations Partial verification We thank the anonymous referees for their helpful comments that improved the quality of the manuscript. 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. 2021-09-20T09:54:00Z 2021-09-20T09:54:00Z 2021-07-19 journal article Roldán-Nofuentes, J.A.; Regad, S.B. Estimation of the Average Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification. Mathematics 2021, 9, 1694. [https://doi.org/10.3390/math9141694] http://hdl.handle.net/10481/70297 10.3390/math9141694 eng http://creativecommons.org/licenses/by/3.0/es/ open access Atribución 3.0 España MDPI