Two-Stage Dynamic Signal Detection: A Theory of Choice, Decision Time, and Confidence
Two-Stage Dynamic Signal Detection: A Theory of Choice, Decision Time, and Confidence
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DOI：
10.1037/a0019737
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发表时间：
2010-07-01
影响因子：
5.4
通讯作者：
Busemeyer, Jerome R.
中科院分区：
文献类型：
--
作者：
Pleskac, Timothy J.;Busemeyer, Jerome R.
认知和决策科学中最常用的三个性能指标是选择，反应或决策时间和信心。我们开发了一个随机游走/扩散理论-2阶段动态信号检测（2DSD）理论，占所有3个措施使用一个共同的底层过程。该模型使用漂移扩散过程来考虑选择和决策时间。为了估计置信度，我们假设证据在选择之后继续积累。然后，法官打断这一过程，将积累的证据归类为置信度等级。该模型解释了所有已知的3个性能指标之间的相互关系。此外，该模型还考虑了感知和一般知识任务中每个变量的分布。该模型的动态性质还揭示了时间压力对选择准确性和信心的调节作用。最后，该模型指定了最佳的解决方案，以提供最快的选择和信心评级为一个给定的水平的选择和信心的准确性。法官的行为方式一致的最佳解决方案时，作出信心的判断。
The 3 most often-used performance measures in the cognitive and decision sciences are choice, response or decision time, and confidence. We develop a random walk/diffusion theory-2-stage dynamic signal detection (2DSD) theory-that accounts for all 3 measures using a common underlying process. The model uses a drift diffusion process to account for choice and decision time. To estimate confidence, we assume that evidence continues to accumulate after the choice. Judges then interrupt the process to categorize the accumulated evidence into a confidence rating. The model explains all known interrelationships between the 3 indices of performance. Furthermore, the model also accounts for the distributions of each variable in both a perceptual and general knowledge task. The dynamic nature of the model also reveals the moderating effects of time pressure on the accuracy of choice and confidence. Finally, the model specifies the optimal solution for giving the fastest choice and confidence rating for a given level of choice and confidence accuracy. Judges are found to act in a manner consistent with the optimal solution when making confidence judgments.