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A marginal‐mean ANOVA approach for analyzing multireader multicase radiological imaging data
Author(s) -
Hillis Stephen L.
Publication year - 2013
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.5926
Subject(s) - statistics , generalization , analysis of variance , computer science , covariance , analysis of covariance , repeated measures design , mathematics , mathematical analysis
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. Copyright © 2013 John Wiley & Sons, Ltd.