Alternatives to a table of criterion values in signal detection theory

Brophy, Alfred L.

doi:10.3758/bf03204400

Cited by 44 publications

(29 citation statements)

References 9 publications

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“…Many authors (e.g., Brophy, 1986) suggest using the formula However, this can be rewritten as False-alarm rate z score plotting the ROC curve in z space, where the axes are z scores rather than probabilities (see Figure 3). Continuing this analogy, the slope and intercept of the line that best fits the z scores in z space are found.…”

Section: F(1-h)mentioning

confidence: 99%

Calculation of signal detection theory measures

Stanislaw

Todorov

1999

Behavior Research Methods, Instruments, & Computers

2,579

2,203

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Signal detection theory (SDT) may be applied to any area of psychology in which two different types of stimuli must be discriminated. Wedescribe several of these areas and the advantages that can be realized through the application of SDT. Three of the most popular tasks used to study discriminability are then discussed, together with the measures that SDT prescribes for quantifying performance in these tasks. Mathematical formulae for the measures are presented, as are methods for calculating the measures with lookup tables, computer software specifically developed for SDTapplications, and general purpose computer software (including spreadsheets and statistical analysis software).Signal detection theory (SOT) is widely accepted by psychologists; the Social Sciences Citation Index cites over 2,000 references to an influential book by Green and Swets (1966) that describes SOT and its application to psychology. Even so, fewer than half ofthe studies to which SOT is applicable actually make use ofthe theory (Stanislaw & Todorov, 1992). One possible reason for this apparent underutilization of SOT is that relevant textbooks rarely describe the methods needed to implement the theory. A typical example is Goldstein's (1996) popular perception textbook, which concludes a nine-page description of SOT with the statement that measures prescribed by SOT "can be calculated ... by means of a mathematical procedure we will not discuss here" (p. 594).The failure of many authors to describe SOT's methods may have been acceptable when lengthy, specialized tables were required to implement the theory. Today, however, readily available computer software makes an SOT analysis no more difficult than a t test. The present paper attempts to demonstrate this and to render SOT available to a larger audience than currently seems to be the case.We begin with a brief overview of SOT, including a description of its performance measures. We then present the formulae needed to calculate these measures. Next, we describe different methods for calculating SOT measures. Finally, we provide sample calculations so that readers can verify their understanding and implementation of the techniques.Weare indebted to

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Section: F(1-h)mentioning

confidence: 99%

Calculation of signal detection theory measures

Stanislaw

Todorov

1999

Behavior Research Methods, Instruments, & Computers

2,579

2,203

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“…d' was used as a measure of discrimination, and C as a measure of bias (Brophy, 1986). These measures were calculated for each participant and each condition.…”

Section: Resultsmentioning

confidence: 99%

Influence of Gaze Direction on Face Recognition: A Sensitive Effect

Daury

2011

PSYCHOL BELG

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This study was aimed at determining the conditions in which eye-contact may improve recognition memory for faces. Different stimuli and procedures were tested in four experiments. The effect of gaze direction on memory was found when a simple "yes-no" recognition task was used but not when the recognition task was more complex (e.g., including "Remember-Know" judgements, cf. Experiment 2, or confidence ratings, cf. Experiment 4). Moreover, even when a "yes-no" recognition paradigm was used, the effect occurred with one series of stimuli (cf. Experiment 1) but not with another one (cf. Experiment 3). The difficulty to produce the positive effect of gaze direction on memory is discussed.

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“…Trained and untrained object trials were analysed, signal detection theory sensitivity index's d' was used as the primary dependent measure (Brophy, 1986). Additionally analyses of RTs were also undertaken, but for ease of exposition are only reported where relevant.…”

Section: Stereo-disparity and View Generalization 13mentioning

confidence: 99%

Stereo Disparity Facilitates View Generalization during Shape Recognition for Solid Multipart Objects

Cristino

Davitt

Hayward

et al. 2015

Quarterly Journal of Experimental Psychology

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Current theories of object recognition in human vision make different predictions about whether the recognition of complex, multipart objects should be influenced by shape information about surface depth orientation and curvature derived from stereo disparity. We examined this issue in five experiments using a recognition memory paradigm in which observers (N = 134) memorized and then discriminated sets of 3D novel objects at trained and untrained viewpoints under either mono or stereo viewing conditions. In order to explore the conditions under which stereo-defined shape information contributes to object recognition we systematically varied the difficulty of view generalization by increasing the angular disparity between trained and untrained views. In one series of experiments, objects were presented from either previously trained views or untrained views rotated (15°, 30°, or 60°) along the same plane. In separate experiments we examined whether view generalization effects interacted with the vertical or horizontal plane of object rotation across 40° viewpoint changes. The results showed robust viewpoint-dependent performance costs: Observers were more efficient in recognizing learned objects from trained than from untrained views, and recognition was worse for extrapolated than for interpolated untrained views. We also found that performance was enhanced by stereo viewing but only at larger angular disparities between trained and untrained views. These findings show that object recognition is not based solely on 2D image information but that it can be facilitated by shape information derived from stereo disparity.

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Alternatives to a table of criterion values in signal detection theory

Cited by 44 publications

References 9 publications

Calculation of signal detection theory measures

Calculation of signal detection theory measures

Influence of Gaze Direction on Face Recognition: A Sensitive Effect

Stereo Disparity Facilitates View Generalization during Shape Recognition for Solid Multipart Objects

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