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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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ASIDT: Adaptive Signal Detection Testing

Authors: B Treutwein;

ASIDT: Adaptive Signal Detection Testing

Abstract

Two-alternative forced choice (2AFC) methods which are routinely used in psychophysics provide criterion-free sensitivity measures but at a high price: 2AFC procedures generally need 2 – 3 times the number of trials than a simple yes/no design to achieve the same level of threshold variability. Similarly, signal detection methods provide measures for criterion and sensitivity, but they require predetermined signal levels for the presented stimuli and also need a large number of trials. ASIDT (adaptive signal detection testing) combines rating responses with an adaptive stimulus placement strategy according to the accelerated stochastic approximation method (see Treutwein, 1995 Vision Research35 2503 – 2522). More specifically, during the course of the experiment the rating responses are collapsed into two groups (yes/no). The border between these two groups is set at the current median of the rating categories actually used by the subject. With the collapsed yes/no responses the stimuli are placed according to accelerated stochastic approximation. This placement strategy is based on very simple rules and distributes the stimulus values asymptotically according to a normal distribution around the median. After the experiment, the rating responses can be used to compute a nonparametric and criterion-free sensitivity measure, the area under the empirical ROC, which is equivalent to the percentage correct in a 2AFC experiment. The usage of ASIDT is demonstrated by psychophysical data.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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