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A Marginal-Mean ANOVA Approach for Analyzing Multireader Multicase Radiological Imaging Data

机译:边缘均值方差分析方法用于分析多读者多病例放射成像数据

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摘要

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 which only requires an understanding of conventional ANOVA methods.
机译:Obuchowski和Rockette(OR)提出的相关误差ANOVA方法已成为分析阅读器性能结果(如多阅读器多案例放射成像数据产生的接收器工作特性曲线下面积)的有用方法。但是,这种方法只是针对逐个案例测试析因研究设计而正式提出的。在本文中,我证明OR模型可​​以看作是边际均方差模型。在此边际均值方差分析框架内查看“或”模型是本研究主题的边际均值方差分析方法的基础。这种方法(1)为OR模型提供了直观的动机,包括其协方差参数约束; (2)提供OR检验统计量和参数估计值及其分布和置信区间的轻松推导; (3)易于将OR程序推广到其他研究设计。特别是,我展示了如何遵循一种只需要了解常规ANOVA方法的算法,就可以轻松地为任何平衡研究设计轻松得出OR型分析公式。

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