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Monte Carlo Validation of the Dorfman-Berbaum-Metz Method Using Normalized Pseudovalues and Less Data-Based Model Simplification

机译：使用归一化的伪值和较少的基于数据的模型简化对Dorfman-Berbaum-Metz方法的蒙特卡罗验证

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摘要

Rationale and ObjectivesTwo problems of the Dorfman-Berbaum-Metz (DBM) method for analyzing multireader ROC studies are that it tends to be conservative and can produce AUC estimates outside the parameter space – i.e., greater than one or less than zero. Recently it has been shown that the problem of AUC (or other accuracy) estimates outside the parameter space can be eliminated by using normalized pseudovalues, and it has been suggested that less data-based model simplification be used. Our purpose is to empirically investigate if these two modifications – normalized pseudovalues and less data-based model simplification – result in improved performance.

机译：基本原理和目标Dorfman-Berbaum-Metz（DBM）方法用于分析多读者ROC研究的两个问题是，它趋于保守，并且可以在参数空间之外（即大于1或小于零）生成AUC估计。最近，已经显示出可以通过使用归一化的伪值来消除参数空间之外的AUC（或其他准确性）估计问题，并且已建议使用较少的基于数据的模型简化。我们的目的是凭经验研究这两种修改（归一化的伪值和较少的基于数据的模型简化）是否导致性能提高。

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期刊名称 other
作者
Stephen L. Hillis; Kevin S. Berbaum;
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作者单位

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年(卷),期 -1(12),12
年度 -1
页码 1534–1541
总页数 16
原文格式 PDF
正文语种
中图分类
关键词
receiver operating characteristic (ROC) curve DBM diagnostic radiology corrected F;

机译：接收机工作特性（ROC）曲线;DBM;放射诊断学;校正后的F;

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Monte Carlo Validation of the Dorfman-Berbaum-Metz Method Using Normalized Pseudovalues and Less Data-Based Model Simplification

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