Dofrman D D, Berbaum K S, Lenth R V
Department of Psychology, University of Iowa, Iowa City 52242, USA.
Acad Radiol. 1995 Jul;2(7):626-33. doi: 10.1016/s1076-6332(05)80129-1.
We evaluated by bootstrapping the conclusions obtained by the Dorfman-Berbaum-Metz (DBM) receiver operating characteristic (ROC) method and by the Toledano-Gatsonis (TG) method on a well-known data set.
We bootstrapped in two ways, resampled cases while holding readers fixed and resampled both cases and readers.
When an analysis of variance of pseudovalues implies that reader variance and all random interactions with treatment are essentially zero, then case-resampling bootstrap and the DBM and TG methods should give the same results. Case-resampling bootstrap and the DBM and TG methods did give highly similar results for both individual readers and the averages over all readers. Both the case-resampling bootstrap and the reader-case resampling bootstrap gave smaller standard errors for group than for individual reader means, thereby providing evidence for a trade-off of readers and cases with regard to precision and power in this data set.
Case-resampling bootstrap provides some justification for the DBM and TG methods.
我们通过自抽样法评估了在一个知名数据集上，采用多夫曼 - 伯鲍姆 - 梅茨（DBM）接收者操作特征（ROC）方法和托莱达诺 - 加特索尼斯（TG）方法所得到的结论。
我们采用两种自抽样方式，在保持读者固定的情况下对病例进行重抽样，以及对病例和读者都进行重抽样。
当对伪值的方差分析表明读者方差以及与治疗的所有随机交互作用基本为零时，那么病例重抽样自抽样法与DBM和TG方法应得出相同的结果。病例重抽样自抽样法与DBM和TG方法对于个体读者以及所有读者的平均值确实给出了高度相似的结果。病例重抽样自抽样法和读者 - 病例重抽样自抽样法对于组均值所给出的标准误差都比对个体读者均值的标准误差小，从而为该数据集中读者和病例在精度与效能方面的权衡提供了证据。
病例重抽样自抽样法为DBM和TG方法提供了一定的合理性依据。
