Elementary Signal Detection Theory

Wickens, Thomas D.

doi:10.1093/acprof:oso/9780195092509.001.0001

Cited by 854 publications

(1,032 citation statements)

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“…2 It is interesting to note that the deviations from the intersection-point criteria locations appear to be in the direction of where optimal criteria would be located (see Wickens, 2002). Because Classes 1 and 6 have small sizes, the optimal criteria should be further to the left for c 1 and …”

Section: Notesmentioning

confidence: 98%

Studies of a Latent‐class Signal‐detection Model for Constructed‐response Scoring

DeCarlo¹

2008

ETS Research Report Series

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Rater behavior in essay grading can be viewed as a signal-detection task, in that raters attempt to discriminate between latent classes of essays, with the latent classes being defined by a scoring rubric. The present report examines basic aspects of an approach to constructed-response (CR) scoring via a latent-class signal-detection model. The model provides a psychological framework for CR scoring and includes rater parameters with a clear cognitive basis. Simulations are used to examine how well rater parameters and latent-class sizes are recovered as well as the accuracy of classification. The relation of rater parameters to agreement statistics and classification accuracy is examined. The effects of using a balanced, incomplete block design are compared to those for a fully crossed design. The model is applied to several ETS datasets.

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Section: Notesmentioning

confidence: 98%

Studies of a Latent‐class Signal‐detection Model for Constructed‐response Scoring

DeCarlo¹

2008

ETS Research Report Series

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“…Following SDT convention, we assume target and distractors elicit Gaussian responses of equal variance (Green, & Swets, 1966;Wickens, 2001). In this case, we set the mean target response to zero and the mean response to each distractor as ± d'.…”

Section: Bayesian Model For Preview Searchmentioning

confidence: 99%

Visuospatial working memory mediates inhibitory and facilitatory guidance in preview search.

Barrett¹,

Shimozaki²,

Jensen³

et al. 2016

Journal of Experimental Psychology: Human Perception and Perfor

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Visual search is faster and more accurate when a subset of distractors is presented before the display containing the target. This "preview benefit" has been attributed to separate inhibitory and facilitatory guidance mechanisms during search. In the preview task the temporal cues thought to elicit inhibition and facilitation provide complementary sources of information about the likely location of the target. In this study, we use a Bayesian Observer model to compare sensitivity when the temporal cues eliciting inhibition and facilitation produce complementary, and competing, sources of information. Observers searched for T-shaped targets among L-shaped distractors in two standard and two preview conditions. In the standard conditions, all the objects in the display appeared at the same time. In the preview conditions, the initial subset of distractors either stayed on the screen or disappeared before the onset of the search display, which contained the target when present. In the latter, the synchronous onset of old and new objects negates the predictive utility of stimulus-driven capture during search. The results indicate observers combine memory-driven inhibition and sensory-driven capture to reduce spatial uncertainty about the target's likely location during search. In the absence of spatially predictive onsets, memorydriven inhibition at old locations persists despite irrelevant sensory change at previewed locations. This result is consistent with a bias towards unattended objects during search via the active suppression of irrelevant capture at previously attended locations.

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“…Negative log β scores reflect a bias to say that the signal was present when it was in fact not present (Wickens, 2002). 2 Finally, we averaged the hits, false alarms, d' and log β for both categories of words.…”

Section: Resultsmentioning

confidence: 99%

“…At Lag 8, the percentage of 0 scores was considerably higher: Note that both scores of 0 and scores of 1 are valid data points, that were replaced solely for the purpose of normalization. As Wickens (2002) points out, it is important to realize that the addition or subtraction of a value like 1 / 1000 is arbitrary. But as we substitute these values for both the neutral and the taboo hits and false alarms, the effect of the substitutions is equal for both categories and can thus not explain our effects.…”

Section: Attentional Blink 11mentioning

confidence: 99%