Applications Of Signal Detection Theory Research Articles

Signal detection theory with item effects

Applications of signal detection theory (SDT) often involve presentations of different items on each trial, such as slides in a medical imaging study or words in a memory study. If factors particular to the items themselves, apart from being a signal or noise, affect observers’ responses, then ‘item effects’ are present. One way to model these effects is to use a latent continuous variable as an item ‘factor’, such as item ‘difficulty’. Details of SDT models with item effects are clarified via derivations of their implied conditional means, variances, and covariances. Intra-item correlations are defined and suggested as measures of the magnitude of item effects. The SDT-item models are simple random coefficient models and can be fit with standard software. More general models, such as item models with mixing and/or with random observer effects, are also considered.

A special issue on applications of Signal Detection Theory to visual perception

A special issue on applications of Signal Detection Theory to visual perception

Extending Effects of Salience and Payoffs on Stimulus Discrimination: An Experimental Simulation of Prescription Checking

This study applied specific aspects of signal detection theory (target salience and decision payoffs) to examine the associations among measured attention and accuracy on a stimulus discrimination task patterned after prescription checking. 85 participants completed the d2 Test of Attention and were assigned to either a control condition with general task instructions or a payoff condition with points accumulated or lost based on ultimate performance. Participants checked simulated product order forms for clerical errors for 40 min. The stimulus set included errors that varied with respect to their ease of detection or salience. Analysis indicated that measured attention was related to performance accuracy and speed as expected. Also decision payoffs significantly increased accuracy on the discrimination task regardless of target salience and discrimination accuracy decreased as the salience of the stimulus mismatches decreased. Implications for real-world applications of signal detection theory to tasks such as prescription checking are explored.

Some contributions of signal detection theory to the analysis of stimulus control in animals

This paper reviews some applications of Signal Detection Theory (SDT) to the quantitative analysis of non-human animal discrimination. The basic detection model is briefly outlined and the separation of sensitivity and bias is illustrated. Several other applications and ideas are reviewed, including the rating method, some implications of signal and criterion variance, and the measurement of ‘guesses’ not encompassed by standard SDT. The conceptual framework and analytic tools of SDT help to clarify processes underlying stimulus control and provide direction to more complete process models.

Signal Detection Theory and Single Observation Designs: Methods and Indices for Advertising Recognition Testing

Most marketing applications of signal detection theory (SDT) produce an estimate of the respondent's memory accuracy based on exposure to a number of advertisements. Marketing practitioners, however, are usually more interested in the performance of an individual advertisement, or elements of that ad. Moreover, advertising recognition paradigms are typically limited to single observations per respondent. The authors present and compare two alternative methodologies that estimate SDT parameters for such designs by pooling recognition performance across respondents. They present two simulations that explore the most efficient methodology and suggest guidelines for selecting appropriate accuracy indices.

Signal Detection Theory and Single Observation Designs: Methods and Indices for Advertising Recognition Testing

Most marketing applications of signal detection theory (SDT) produce an estimate of the respondent's memory accuracy based on exposure to a number of advertisements. Marketing practitioners, howeve...

A Signal Detection Theory Analysis of a Driving Decision Task: Spatial Gap Acceptance

Applications of signal detection theory (SDT) in the study of road-users behavior were tested in both real and laboratory settings. The field study used a gap-acceptance task with 3 levels of experimentally produced frustration. The laboratory simulation used a parking task, again with 3 levels of frustration. In addition, a multidimensional analysis of driver's subjective road experience and behavior aided in the interpretation of one of the experimental measures. Successful applications of SDT techniques to the analysis of several traffic problems are demonstrated, and future applications are suggested.

The Use of Signal Detection Theory in Research on Human-Computer Interaction

The use of signal detection theory (SDT) in evaluating attentional and decision-making performance in the context of human-computer interaction is reviewed. SDT provides a means for distinguishing between accuracy and criterion setting in decision-making environments. This is useful in evaluating the effectiveness of the decision-making performance of an intelligent machine, a human user, or a human-machine system. SDT is also useful in deciding how best to allocate subtasks and functions in human-computer monitoring systems. Applications of SDT to the evaluation of rule bases in expert systems and the design of computer assistance in human-computer monitoring are discussed.

A review of some unusual applications of signal detection theory

A review of some unusual applications of signal detection theory

Applications of Signal Detection Theory in Monitoring Performance and Medical Diagnosis

Signal detection theory (SDT) provides a means for distinguishing between accuracy and decision strategies in evaluating observer performance in decision-making tasks. This is useful in determining which general human engineering principles, for example, design, or selection and training, are likely to be effective in a particular situation. Two illustrative areas of application are discussed: (1) Performance decrements in monitoring (vigilance) tasks result either from a decrement in observer sensitivity or from changes in decision criteria. A taxonomic approach is outlined which predicts which of these performance trends will occur in a particular monitoring situation. This enables an identification of those cases where sensitivity decrements occur, for which design changes may be needed and where training techniques are unlikely to be helpful in enhancing performance. (2) Poor reader performance in medical diagnosis may result from inappropriate reporting criteria, especially when disease prevalence and decision goals vary. A study is reported in which staff radiologists, but not radiology residents, were found to vary their reporting criteria appropriately in response to a change in disease prevalence. Staff radiologists were superior to the residents in disease detection and classification, but the residents were not significantly worse if both first and second choice diagnoses were analyzed. ROC measures of diagnostic accuracy were independent of disease prevalence and reporting criteria. The results have implications for the identification of training criteria and the assessment of system accuracy in diagnostic radiology. These two studies illustrate the general usefulness of SDT in identifying target areas for the application of human engineering principles.

An APL program for calculating signal detection indices

Since Green and Swets' Signal Detection Theory and Psychophysics (1966), numerous books and articles have developed statistical decision or signal detection theory (SOT), for example, Egan (1975), Egan and Clarke (1966), Green and Swets (1966jI974), McNicol (1972), and Swets (1973). In addition, the. model has been applied to diverse areas of research: an~al as well as human psychophysics, memory, personality, learning, medicine, and behavioral pharmacology (Aiken, 1969; Appel & Dykstra, 1977; Lloyd & Appel, 1976; Price, 1966;Swets, 1969; Terman, 1970). In brief, SOT attempts to differentiate statistically between effects on discrimination of variables related to physical properties of the stimulus (sensitivity) and effects of variables related to characteristics of the response (criterion or bias). In this attempt, numerous parametric as well as nonparametric indices of both sensitivity and bias estimation have been developed (Dusoir, 1975; Green & Swets, 1966jI974;Grier, 1971; Hodos, 1970; Pollack, 1970; Pollack & Hsieh, 1969; Pollack & Norman, 1964). Of these, the most familiar parametric measures are d' (sensitivity) and (3 or In{3 (bias). The most familiar nonparametric measures are A' or P(I) (sensitivity) and B'H (bias). In applications of SOT, a yes-no procedure is often employed. In this paradigm a subject reports either that a stimulus has (R+) or has not (R-) occurred, given that the stimulus has (S+) or has not (S-) been presented. All possible outcomes can be represented as four relative frequencies, that is, HIT = fr(R+jS+), MISS = fr(R-jS+), False Alarm (FA) = fr(R+jS-), and Correct Rejection (CR) = fr(R-jS-). From these frequencies, conditioned probabilities, that is, p(R+/S+) and p(R+jS-), can be determined. When sample size is not too large or the number of observations is limited, indices of both sensitivity and bias can be calculated in a reasonable amount of time; moreover, tables of both d' and {3 are available for some, but not all, conditional probabilities (Freeman, 1973). A serious problem arises when parametric indices are used and the data a!e inconsistent with the assumptions of the model, that IS, Thurstone's case V of underlying normal distribution

Radiographic applications of signal detection theory.

Receiver operating characteristic (ROC) curves describe observer performance in the detection of small noiselimited signals such as the image of a 2 mm Lucite bead against a background of radiographic mottle. A combination of a fast-speed screen and normal-speed :film yields greater signal detectability than a combination of a medium-speed screen and fast-speed film.

Some Applications of Signal Detection Theory to Paedo-Audiology

IntroductionThe majority of reports on auditory behaviour in the infant and young child give inadequate information about test conditions and lack careful scientific validation of the findings. The authors agree with Fisch (1969) and Eisenberg (1969) who argue that paedo-audio-logical procedures in current use are empirical rather than experimental. In an attempt to offset this type of approach the authors have explored certain diagnostic procedures by statistical analyses with particular reference to signal detection theory.

Applications of Signal Detection Theory to Audiometry

Applications of Signal Detection Theory to Audiometry