title: A marginal-mean ANOVA approach for analyzing multireader multicase radiological imaging data.
abstract: 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.
authors.affiliation: Departments of Radiology and Biostatistics, The University of Iowa, 3710 Medical Laboratories, 200 Hawkins Drive, Iowa City, IA 52242-1077, U.S.A.; Comprehensive Access and Delivery Research and Evaluation (CADRE) Center, Iowa City VA Health Care System, IA 52242-1077, U.S.A.
authors.forename: Stephen L
authors.initials: SL
authors.lastname: Hillis
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D019540:Area Under Curve; D006801:Humans; D015233:Models, Statistical; D012372:ROC Curve; D011871:Radiology / Q000379:methods*
keywords: correlated ANOVA; diagnostic radiology; receiver operating characteristic (ROC) curve
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