Non-inferiority test and confidence interval for the difference in correlated proportions in diagnostic procedures based on multiple raters.

The efficacy of diagnostic procedures is generally evaluated on the basis of the results from multiple raters. However, there are few adequate methods of performing non-inferiority tests with confidence intervals to compare the accuracies (sensitivities or specificities) when multiple raters are considered. We propose new statistical methods for comparing the accuracies of two diagnostic procedures in a non-inferiority trial, on the basis of the results from multiple independent raters who are also independent of the study centers. We consider a study design in which each patient is subjected to two diagnostic procedures and all images are read by all raters. By assuming a multinomial distribution for matched-pair categorical data arising from the study design, we derive a score-based full menu, that is, a non-inferiority test, confidence interval and sample size formula, for inference of the difference in correlated proportions between the two diagnostic procedures. We conduct Monte Carlo simulation studies to examine the validity of the proposed methods, which showed that the proposed test has a size closer to the nominal significance level than a Wald-type test and that the proposed confidence interval has better empirical coverage probability than a Wald-type confidence interval. We illustrate the proposed methods with data from a study of diagnostic procedures for the diagnosis of oesophageal carcinoma infiltrating the tracheobronchial tree.