Estimation of the Average Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification
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MDPI
Materia
Average kappa coefficient Missing data Multiple imputation by chained equations Partial verification
Fecha
2021-07-19Referencia bibliográfica
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]
Resumen
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.