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Signal detection theory with finite mixture distributions: Theoretical developments with applications to recognition memory.
Authors:DeCarlo   Lawrence T.
Abstract: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. (PsycINFO Database Record (c) 2010 APA, all rights reserved)
Keywords:signal detection theory   finite mixture distributions   recognition memory
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