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- W1967839092 abstract "Abstract By generalizing properties of the standard normal model of signal detection theory, we are able to characterize symmetric, partially stable random variables in terms of a pair of observable relations coupling yes-no and forced-choice paradigms. One of these relations is provided by the ‘area theorem’: the area subtended by a receiver operating characteristics equals the probability of a correct response in the corresponding forced-choice task. The other relation involves the algebraic notion of bisymmetry. It turns out that most partially stable random variables are actually stable . Accordingly we can interpret our results as characterizing detection models in which ‘signal’ and ‘noise’ random variables arise as sums of many small independent contributions." @default.
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- W1967839092 date "1992-04-01" @default.
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- W1967839092 title "Characterizing random variables in the context of signal detection theory" @default.
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- W1967839092 doi "https://doi.org/10.1016/0165-4896(92)90015-w" @default.
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