Converting between measures of slope of the psychometric function - Attention, Perception, & Psychophysics
- ️Strasburger, Hans
- ️Thu Nov 01 2001
Abstract
The psychometric function’s slope provides information about the reliability of psychophysical threshold estimates. Furthermore, knowing the slope allows one to compare, across studies, thresholds that were obtained at different performance criterion levels. Unfortunately, the empirical validation of psychometric function slope estimates is hindered by the bewildering variety of slope measures that are in use. The present article provides conversion formulas for the most popular cases, including the logistic, Weibull, Quick, cumulative normal, and hyperbolic tangent functions as analytic representations, in both linear and log coordinates and to different log bases, the practical decilog unit, the empirically based interquartile range measure of slope, and slope in aď representation of performance.
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References
Chauhan, B. C., & House, P. H. (1991). Intratest variability in conventional and high-pass resolution perimetry.Ophthalmology,98, 79–83.
Chauhan, B. C., Tompkins, J. D., LeBlanc, R. P., & McCormick, T. A. (1993). Characteristics of frequency-of-seeing curves in normal subjects, patients with suspected glaucoma, and patients with glaucoma.Investigative Ophthalmology & Visual Science,34, 3534–3540.
Elliot, P. B. (1964). Tables ofď. In J. A. Swets (Ed.),Signal detection and recognition by human observers (pp. 651–684). New York: Wiley.
Foster, D. H. (1986). Estimating the variance of a critical stimulus level from sensory performance data.Biological Cybernetics,53, 189–194.
Green, D. M., & Swets, J. A. (1966).Signal detection theory and psychophysics. New York: Wiley. [Reprint edition (1988) by Peninsula Publishing, Los Altos, CA].
Harvey, L. O., Jr. (1997). Efficient estimation of sensory thresholds with ML-PEST.Spatial Vision,11, 121–128.
King-Smith, P. E., & Rose, D. (1997). Principles of an adaptive method for measuring the slope of the psychometric functions.Vision Research,37, 1595–1604.
Klein, S. A. (2001). Measuring, estimating and understanding the psychometric function: A commentary.Perception & Psychophysics,63, 1421–1455.
Kontsevich, L. L., & Tyler, C. W. (1999). Bayesian adaptive estimation of psychometric slope and threshold.Vision Research,39, 2729–2737.
Leek, M. R., Hanna, T. E., & Marshall, L. (1992). Estimation of psychometric functions from adaptive tracking procedures.Perception & Psychophysics,51, 247–256.
Patterson, V. H., Foster, D. H., & Heron, J. R. (1980). Variability of visual threshold in multiple sclerosis: Effect of background luminance on frequency of seeing.Brain,103, 139–147.
Pelli, D. G. (1985). Uncertainty explains many aspects of visual contrast detection and discrimination.Journal of the Optical Society of America A,2, 1508–1532.
Quick, R. F. A. (1974). A vector magnitude model of contrast detection.Kybernetic,16, 65–67.
Strasburger, H. (2001). Invariance of the psychometric function for letter recognition across the visual field.Perception & Psychophysics,63, 1356–1376.
Treutwein, B., & Strasburger, H. (1999). Fitting the psychometric function.Perception & Psychophysics,61, 87–106.
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Ludwig-Maximilians-Universität, München, Germany
Hans Strasburger
Otto-von-Guericke-Universität, Magdeburg, Germany
Hans Strasburger
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Strasburger, H. Converting between measures of slope of the psychometric function. Perception & Psychophysics 63, 1348–1355 (2001). https://doi.org/10.3758/BF03194547
Received: 23 September 1998
Accepted: 04 March 2001
Issue Date: November 2001
DOI: https://doi.org/10.3758/BF03194547