Asymptotic hypothesis test to simultaneously compare the weighted kappa coefficients of multiple binary diagnostic tests in the presence of ignorable missing data

• Published in: Journal of statistical computation and simulation Vol. 84; no. 2; pp. 273 - 289
• Main Authors: Nofuentes, J.A. Roldán, Jiménez, A.E. Marín, Castillo, J.D. Luna del
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 01.02.2014; Taylor & Francis Ltd
• Subjects: Asymptotic properties; Cardiovascular disease; Comparative analysis; Diagnostic tests; Estimating techniques; Hochberg's method; Holm's method; ignorable missing data; partial verification; Simulation; weighted kappa coefficient
• ISSN: 0094-9655; 1563-5163
• DOI: 10.1080/00949655.2012.706300

The weighted kappa coefficient of a binary diagnostic test is a measure of the beyond-chance agreement between the diagnostic test and the gold standard, and is a measure that allows us to assess and compare the performance of binary diagnostic tests. In the presence of partial disease verification, the comparison of the weighted kappa coefficients of two or more binary diagnostic tests cannot be carried out ignoring the individuals with an unknown disease status, since the estimators obtained would be affected by verification bias. In this article, we propose a global hypothesis test based on the chi-square distribution to simultaneously compare the weighted kappa coefficients when in the presence of partial disease verification the missing data mechanism is ignorable. Simulation experiments have been carried out to study the type I error and the power of the global hypothesis test. The results have been applied to the diagnosis of coronary disease.