Signal detection theory with finite mixture distributions: Theoretical developments with applications to recognition memory
Signal detection theory with finite mixture distributions: Theoretical developments with applications to recognition memory
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DOI：
10.1037//0033-295x.109.4.710
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发表时间：
2002-10-01
影响因子：
5.4
通讯作者：
DeCarlo, LT
中科院分区：
文献类型：
--
作者：
DeCarlo, LT
扩展的信号检测理论（SDT），将混合物的基本分布。混合物的动机可以是这样的想法，即只有当观察者注意到信号时，信号的呈现才会移动底层分布的位置;否则，分布不会移动或仅部分移动。因此，具有信号呈现的试验由2个（或更多个）潜在试验类别的混合物组成。混合物SDT提供了一个一般的理论框架，提供了一个新的角度对一些发现。例如，混合SDT提供了不等方差信号检测模型的替代方案;正如最近的研究中发现的那样，它还可以解释非线性正态接收器操作特征曲线。
An extension of signal detection theory (SDT) that incorporates mixtures of the underlying distributions is presented. The mixtures can be motivated by the idea that a presentation of a signal shifts the location of an underlying distribution only if the observer is attending to the signal; otherwise, the distribution is not shifted or is only partially shifted. Thus, trials with a signal presentation consist of a mixture of 2 (or more) latent classes of trials. Mixture SDT provides a general theoretical framework that offers a new perspective on a number of findings. For example, mixture SDT offers an alternative to the unequal variance signal detection model; it can also account for nonlinear normal receiver operating characteristic curves, as found in recent research.