  Positive and negative likelihood ratios are parameters which are used to
assess and compare the effectiveness of binary diagnostic tests. Both
parameters only depend on the sensitivity and specificity of the diagnostic
test and are equivalent to a relative risk. This article studies the comparison
of the likelihood ratios of two binary diagnostic tests subject to a paired
design through confidence intervals. Six approximate confidence intervals are
presented for the ratio of the likelihood ratios, and simulation experiments
are carried out to study the coverage probabilities and the average lengths of
the intervals considered, and some general rules of application are proposed. A
method is also proposed to determine the sample size necessary to estimate the
ratio between the likelihood ratios with a determined precision. The results
were applied to the diagnosis of coronary artery disease.
