A marginal-mean ANOVA approach for analyzing multireader multicase radiological imaging data.

The correlated-error ANOVA method proposed by Obuchowski and Rockette (OR) has been a useful procedure for analyzing reader-performance outcomes, such as the area under the receiver-operating-characteristic curve, resulting from multireader multicase radiological imaging data. This approach, however, has only been formally derived for the test-by-reader-by-case factorial study design. In this paper, I show that the OR model can be viewed as a marginal-mean ANOVA model. Viewing the OR model within this marginal-mean ANOVA framework is the basis for the marginal-mean ANOVA approach, the topic of this paper. This approach (1) provides an intuitive motivation for the OR model, including its covariance-parameter constraints; (2) provides easy derivations of OR test statistics and parameter estimates, as well as their distributions and confidence intervals; and (3) allows for easy generalization of the OR procedure to other study designs. In particular, I show how one can easily derive OR-type analysis formulas for any balanced study design by following an algorithm that only requires an understanding of conventional ANOVA methods.