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

机译:边缘均方差分析方法用于分析多阅读器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 that 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的面积)的有用方法。但是,这种方法只是针对逐例测试析因研究设计而正式提出的。在本文中,我证明了OR模型可​​以看作是边际均方差模型。在此边际均方差分析框架内查看“或”模型是本研究主题的边际均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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