Monte Carlo validation of a multireader method for receiver operating characteristic discrete rating data: factorial experimental design

Abstract

Rationale and objectives: The authors conducted a series of null-case Monte Carlo simulations to evaluate the Dorfman-Berbaum-Metz (DBM) method for comparing modalities with multireader receiver operating characteristic (ROC) discrete rating data.

Materials and methods: Monte Carlo simulations were performed by using discrete ratings on fully crossed factorial designs with two modalities and three, five, and 10 hypothetical readers. The null hypothesis was true for all simulations. The population ROC areas, latent variable structures, case sample sizes, and normal/abnormal case sample ratios used in another study were used in these simulations.

Results: For equal allocation ratios and small (Az = 0.702) and moderate (Az = 0.855) ROC areas, the empirical type I error rate closely matched the nominal alpha level. For very large ROC areas (Az = 0.961), however, the empirical type I error rate was somewhat smaller than the nominal alpha level. This conservatism increased with decreasing case sample size and asymmetric normal/abnormal case allocation ratio. The empirical type I error rate was sometimes slightly larger than the nominal alpha level with many cases and few readers, where there was large residual, relatively small treatment-by-case interaction and relatively large treatment-by-reader interaction.

Conclusion: The results suggest that the DBM method provides trustworthy alpha levels with discrete ratings when the ROC area is not too large and case and reader sample sizes are not too small. In other situations, the test tends to be somewhat conservative or slightly liberal.