scholarly journals Predicting individual false alarm rates and signal detection theory: A role for remembering

2000 ◽  
Vol 28 (8) ◽  
pp. 1347-1356 ◽  
Author(s):  
Ian G. Dobbins ◽  
Wayne Khoe ◽  
Andrew P. Yonelinas ◽  
Neal E. A. Kroll
Keyword(s):  
Signal Detection ◽  
False Alarm ◽  
Signal Detection Theory ◽  
Detection Theory ◽  
False Alarm Rates

Measures and Interpretations of Vigilance Performance: Evidence against the Detection Criterion

1998 ◽  
Vol 40 (4) ◽  
pp. 601-623 ◽  
Author(s):  
J. D. Balakrishnan
Keyword(s):  
Signal Detection ◽  
False Alarm ◽  
Traffic Control ◽  
Signal Detection Theory ◽  
Vigilance Task ◽  
Detection Theory ◽  
Time On Task ◽  
Signal Rate ◽  
Detection Criterion ◽  
False Alarm Rates

Operators′ performance in a vigilance task is often assumed to depend on their choice of a detection criterion. When the signal rate is low this criterion is set high, causing the hit and false alarm rates to be low. With increasing time on task the criterion presumably tends to increase even further, thereby further decreasing the hit and false alarm rates. Virtually all of the empirical evidence for this simple interpretation is based on estimates of the bias measure β from signal detection theory. In this article, I describe a new approach to studying decision making that does not require the technical assumptions of signal detection theory. The results of this new analysis suggest that the detection criterion is never biased toward either response, even when the signal rate is low and the time on task is long. Two modifications of the signal detection theory framework are considered to account for this seemingly paradoxical result. The first assumes that the signal rate affects the relative sizes of the variances of the information distributions; the second assumes that the signal rate affects the logic of the operator's stopping rule. Actual or potential applications of this research include the improved training and performance assessment of operators in areas such as product quality control, air traffic control, and medical and clinical diagnosis.

Sensitivity and Bias in the Resolution of Stream-Bounce Stimuli

Perception ◽  
2016 ◽  
Vol 46 (2) ◽  
pp. 178-204 ◽  
Author(s):  
Mick Zeljko ◽  
Philip M. Grove
Keyword(s):  
Experimental Design ◽  
Signal Detection ◽  
False Alarm ◽  
Signal Detection Theory ◽  
Detection Theory ◽  
Correct Rejection ◽  
Visual Displays ◽  
Signal Discrimination ◽  
Motion Sequence ◽  
Significant Change

The audiovisual stream-bounce effect refers to the resolution of ambiguous motion sequences as streaming or bouncing depending on the presence or absence of a sound. We used a novel experimental design and signal detection theory (SDT) to determine its sensory or decisional origins. To account for issues raised by Witt et al. on the interpretation of SDT results, we devised a pure signal detection (as opposed to signal discrimination) paradigm and measured participants’ sensitivity and criterion when detecting a weak tone concurrent with objectively streaming or bouncing visual displays. We observed no change in sensitivity but a significant change in criterion with participants’ criterion more liberal with bouncing targets than for streaming targets with. In a second experiment, we tasked participants with detecting a weak tone in noise while viewing an ambiguous motion sequence. They also indicated whether the targets appeared to stream or bounce. Participants’ reported equivalent, mostly bouncing responses for hit and false alarm trials, and equivalent, mostly streaming responses for correct rejection and miss trials. Further, differences in participants’ sensitivity and criterion measures for detecting tones in subjectively streaming compared to subjectively bouncing targets were inconsistent with sensory factors. These results support a decisional account of the sound-induced switch from mostly streaming to mostly bouncing responses in audiovisual stream-bounce displays.

A Computer Program Demonstrating the Effect of the Payoff Matrix on the Signal Detection Measure, Beta

1994 ◽  
Vol 21 (2) ◽  
pp. 113-115 ◽  
Author(s):  
Janet D. Larsen
Keyword(s):  
Computer Program ◽  
Signal Detection ◽  
False Alarm ◽  
Response Bias ◽  
Signal Detection Theory ◽  
Visual Display ◽  
Payoff Matrix ◽  
Detection Theory ◽  
Basic Concepts ◽  
Hit Rates

The computer program described in this article demonstrates the basic concepts of signal detection theory and illustrates the effect of changes in the payoff matrix on beta, a measure of response bias. Observers attempt to identify the trials on which there was a signal in a noisy visual display. They earn or lose points for correct or incorrect answers. After three sets of 100 trials, with a different payoff matrix for each set, the program provides observers with their hit rates, false alarm rates, d' scores, and beta scores for the three sets of trials, as well as the total points they have earned for the 300 trials. The program runs on MS-DOS machines and does not require a computer with graphics capabilities.

So, Whatever Happened to Signal Detection Theory?

1995 ◽  
Vol 40 (10) ◽  
pp. 972-972
Author(s):  
Jerome R. Busemeyer
Keyword(s):  
Signal Detection ◽  
Signal Detection Theory ◽  
Detection Theory

Application of Fuzzy Signal Detection Theory to vigilance: The effect of criterion shifts

2003 ◽  
Author(s):  
Shawn C. Stafford ◽  
James L. Szalma ◽  
Peter A. Hancock ◽  
Mustapha Mouloua
Keyword(s):  
Signal Detection ◽  
Signal Detection Theory ◽  
Detection Theory ◽  
Criterion Shifts
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