Signal detection theory (SDT) plays a central role in the characterization of human judgments in a wide range of domains, most prominently in recognition memory. But despite its success, many of its fundamental properties are often misunderstood, especially when it comes to its testability. The present work examines five main properties that are characteristic of existing SDT models of recognition memory: (a) random-scale representation, (b) latent-variable independence, (c) likelihood-ratio monotonicity, (d) ROC function asymmetry, and (e) nonthreshold representation. In each case, we establish testable consequences and test them against data collected in the appropriately designed recognition-memory experiment. We also discuss the connection between yes–no, forced-choice, and ranking judgments. This connection introduces additional behavioral constraints and yields an alternative method of reconstructing yes–no ROC functions. Overall, the reported results provide a strong empirical foundation for SDT modeling in recognition memory. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

中文翻译：

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测试识别记忆中信号检测理论的基础。

信号检测理论 (SDT) 在广泛领域的人类判断表征中发挥着核心作用，在识别记忆中最为突出。但是，尽管它取得了成功，但它的许多基本属性经常被误解，尤其是在它的可测试性方面。目前的工作检查了现有识别记忆 SDT 模型的五个主要特性：（a）随机尺度表示，（b）潜在变量独立性，（c）似然比单调性，（d）ROC 函数不对称性，以及(e) 非阈值表示。在每种情况下，我们都会建立可测试的结果，并根据在适当设计的识别记忆实验中收集的数据对其进行测试。我们还讨论了是-否、强制选择和排名判断之间的联系。这种连接引入了额外的行为约束，并产生了另一种重建 yes-no ROC 函数的方法。总体而言，报告的结果为识别记忆中的 SDT 建模提供了强有力的经验基础。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）