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Grice-Representability of Response Time Distribution Families

Published online by Cambridge University Press:  01 January 2025

Ehtibar N. Dzhafarov*
Affiliation:
University of Illinois at Urbana-Champaign The Beckman Institute For Advanced Science and Technology
*
Requests for reprints should be sent to Ehtibar N. Dzhafarov, Department of Psychology, University of Illinois at Urbana-Champaign, 603 East Daniel Street, Champaign, IL 61820.

Abstract

Any family of simple response time distributions that correspond to different values of stimulation variables can be modeled by a deterministic stimulation-dependent process that terminates when it crosses a randomly preset criterion. The criterion distribution function is stimulation-independent and can be chosen arbitrarily, provided it is continuous and strictly increasing. Any family of N-alternative choice response time distributions can be modeled by N such process-criterion pairs, with response choice and response time being determined by the process that reaches its criterion first. The joint distribution of the N criteria can be chosen arbitrarily, provided it satisfies certain unrestrictive conditions. In particular, the criteria can be chosen to be stochastically independent. This modeling scheme, therefore, is a descriptive theoretical language rather than an empirically falsifiable model. The only role of the criteria in this theoretical language is to numerically calibrate the ordinal-scale axes for the deterministic response processes.

Type
Original Paper
Copyright
Copyright © 1993 The Psychometric Society

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Footnotes

The author is indebted to Richard Schweickert, James Townsend, and Duncan Luce for valuable comments and criticism.

References

Ashby, F. G. (1982). Deriving exact predictions from the cascade model. Psychological Review, 89, 599607.CrossRefGoogle Scholar
Coles, M. G. H., Gratton, G., Bashore, T. R., Eriksen, C. W., Donchin, E. (1985). A psychophysiological investigation of the continuous flow model of human information processing. Journal of Experimental Psychology: Human Perception and Performance, 11, 529553.Google ScholarPubMed
Cronin, J. (1980). Differential equations: Introduction and qualitative theory, New York: Marcel Dekker.Google Scholar
Dzhafarov, E. N. (1992). The structure of simple reaction time to step-function signals. Journal of Mathematical Psychology, 36, 235268.CrossRefGoogle Scholar
Eriksen, C. W., Schultz, D. W. (1979). Information processing in visual search: A continuous flow conception and experimental results. Perception & Psychophysics, 25, 249263.CrossRefGoogle ScholarPubMed
Everitt, B., Hand, D. J. (1981). Finite mixture distributions, New York: Chapman and Hall.CrossRefGoogle Scholar
Feller, W. (1968). An introduction to probability theory and its applications, Vol. 1, New York: Wiley.Google Scholar
Green, D. M., Luce, R. D. (1974). Timing and counting mechanisms in auditory discrimination and reaction time. In Krantz, D. H., Atkinson, R. C., Luce, R. D., Suppes, P. (Eds.), Contemporary developments in Mathematical Psychology, Vol. 2 (pp. 372415). San Francisco: Freeman.Google Scholar
Grice, G. R. (1968). Stimulus intensity and response evocation. Psychological Review, 75, 359373.CrossRefGoogle ScholarPubMed
Grice, G. R. (1972). Application of a variable criterion model to auditory reaction time as a function of the type of catch trial. Perception & Psychophysics, 12, 103107.CrossRefGoogle Scholar
Grice, G. R., Canham, L., Boroughs, J. M. (1984). Combination rule for redundant information in reaction time tasks with divided attention. Perception & Psychophysics, 35, 451463.CrossRefGoogle ScholarPubMed
Grice, G. R., Nullmeyer, R., Spiker, V. A. (1982). Human reaction time: Toward a general theory. Journal of Experimental Psychology: General, 111, 135153.CrossRefGoogle Scholar
LaBerge, D. A. (1962). A recruitment theory of simple behavior. Psychometrica, 27, 375396.CrossRefGoogle Scholar
Laming, D. R. J. (1968). Information theory of choice-reaction times, London: Academic Press.Google Scholar
Link, S. W. (1975). The relative judgement theory of two-choice response time. Journal of Mathematical Psychology, 12, 114135.CrossRefGoogle Scholar
Luce, R. D. (1986). Response times, New York: Oxford University Press.Google Scholar
Marley, A. A. J. (1992). A selective review of recent characterizations of stochastic choice models using distribution and functional equation techniques. Mathematical Social Sciences, 23, 529.CrossRefGoogle Scholar
Marley, A. A. J., Colonius, H. (1992). The “horse race” random utility model for choice probabilities and reaction times, and its competing risk interpretation. Journal of Mathematical Psychology, 36, 120.CrossRefGoogle Scholar
Matveev, N. M. (1974). Methods of integration of ordinary differential equations, Minsk: Vysheishaia Shkola (in Russian)Google Scholar
McClelland, J. L. (1979). On the time relations of mental processes: An examination of systems of processes in cascade. Psychological Review, 86, 287330.CrossRefGoogle Scholar
McGill, W. (1963). Stochastic latency mechanisms. In Luce, R. D., Galanter, E. (Eds.), Handbook of mathematical psychology, Vol. 1 (pp. 309360). New York: Wiley.Google Scholar
Pacut, A. (1977). Some properties of threshold models of reaction latency. Biological Cybernetics, 28, 6372.CrossRefGoogle Scholar
Petrovski, I. G. (1964). Lectures on theory of ordinary differential equations, Moscow: Nauka (in Russian)Google Scholar
Pike, R. (1973). Response latency models for signal detection. Psychological Review, 80, 5368.CrossRefGoogle ScholarPubMed
Ratcliff, R. (1978). A theory of memory retrieval. Psychological Review, 85, 59108.CrossRefGoogle Scholar
Schweickert, R. (1985). Separable effects of factors on activation functions in discrete and continuous models: d′ and evoked potentials. Psychological Bulletin, 106, 318328.CrossRefGoogle Scholar
Townsend, J. T. (1976). Serial and within-stage independent parallel model equivalence on the minimum completion time. Journal of Mathematical Psychology, 14, 219238.CrossRefGoogle Scholar
Townsend, J. T., Ashby, F. G. (1983). The stochastic modeling of elementary psychological processes, Cambridge: Cambridge University Press.Google Scholar
Vickers, D. (1970). Evidence for an accumulator model of psychophysical discrimination. Ergonomics, 13, 3758.CrossRefGoogle ScholarPubMed