Binary ROCs in Perception and Recognition Memory Are Curved
Binary ROCs in Perception and Recognition Memory Are Curved
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DOI：
10.1037/a0024957
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发表时间：
2012-01-01
影响因子：
2.6
通讯作者：
Rotello, Caren M.
中科院分区：
文献类型：
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作者：
Dube, Chad;Rotello, Caren M.
在识别记忆中，一个经典的发现是接收者的工作特征(ROC)是曲线的。这被用来支持离散状态模型上的信号检测理论(SDT)的基本假设，例如预测线性ROC的双高阈值模型(2HTM)。然而，最近，Broder和Schutz(2009)对这一论点提出了质疑，他们指出，支持SDT的大多数数据都涉及信心评级。作者认为，某些类型的评分表的使用可能会导致ROC曲线，即使生成过程在本质上是有阈值的。从这个角度来看，只有通过实验偏差操作构建的ROC才能用于区分不同的模型。Broder和Schutz进行了荟萃分析和新的实验，使用二进制(是-否)ROC对SDT和2HTM进行了比较，发现这些函数中的许多都是线性的，支持SDT的2HTM。我们检查了Broder和Schutz报告的所有数据，指出了他们在方法、分析和结论方面的重要局限性。我们报告了一个新的荟萃分析和两个新的实验来更密切地研究这个问题，同时避免了Broder和Schutz的研究的局限性。这些新数据表明，二进制ROC在识别上是弯曲的，这与之前在感知和推理方面的发现一致。我们的结果支持支持SDT的经典论点，并表明评级ROC的曲率不是特定于任务的。我们推荐评级程序，并建议谨慎对待基于阈值模型的分析。
In recognition memory, a classic finding is that receiver operating characteristics (ROCs) are curvilinear. This has been taken to support the fundamental assumptions of signal detection theory (SDT) over discrete-state models such as the double high-threshold model (2HTM), which predicts linear ROCs. Recently, however, Broder and Schutz (2009) challenged this argument by noting that most of the data on which support for SDT is based have involved confidence ratings. The authors argued that certain types of rating scale usage may result in curved ROCs even if the generating process is thresholded in nature. From this point of view, only ROCs constructed via experimental bias manipulations are useful for discriminating between the models. Broder and Schutz conducted a meta-analysis and new experiments that compared SDT and the 2HTM using binary (yes-no) ROCs and found that many of these functions were linear, supporting 2HTM over SDT. We examine all the data reported by Broder and Schutz, noting important limitations in their methodology, analyses, and conclusions. We report a new meta-analysis and 2 new experiments to examine the issue more closely while avoiding the limitations of Broder and Schutz's study. These new data indicate that binary ROCs are curved in recognition, consistent with previous findings in perception and reasoning. Our results support classic arguments in favor of SDT and indicate that curvature in ratings ROCs is not task specific. We recommend the ratings procedure and suggest that analyses based on threshold models be treated with caution.