  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 depends on the sensitivity and specificity of the diagnostic test, on the
disease prevalence and on the relative importance between the false positives
and the false negatives. This article studies the comparison of the weighted
kappa coefficients of two binary diagnostic tests subject to a paired design
through confidence intervals. Three asymptotic confidence intervals are studied
for the difference between the parameters and five other intervals for the
ratio. Simulation experiments were carried out to study the coverage
probabilities and the average lengths of the intervals, giving some general
rules for application. A method is also proposed to calculate the sample size
necessary to compare the two weighted kappa coefficients through a confidence
interval. A program in R has been written to solve the problem studied and it
is available as supplementary material. The results were applied to a real
example of the diagnosis of malaria.
