Fitting the psychometric function

Perception and Psychophysics

Volumn 61, Issue 1, 1999, Pages 87-106

  Treutwein, Bernhard ^a   Strasburger, Hans ^b  

^a UNIVERSITY OF MUNICH   (Germany)

^b OTTO VON GUERICKE UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BAYES THEOREM; EPIDEMIOLOGY; HUMAN; MONTE CARLO METHOD; PROBABILITY; PSYCHOMETRY; PSYCHOPHYSICS; STATISTICAL MODEL;

BAYES THEOREM; BIAS (EPIDEMIOLOGY); HUMANS; LIKELIHOOD FUNCTIONS; MONTE CARLO METHOD; PROBABILITY; PSYCHOMETRICS; PSYCHOPHYSICS;

EID: 0032602354     PISSN: 00315117     EISSN: None     Source Type: Journal    
DOI: 10.3758/BF03211951     Document Type: Article

References (51)

1. AGRESTI, A. (1990). Categorical data analysis. New York: Wiley.
2. BROWN, K. M., & DENNIS, J. E. J. (1972). Derivative free analogues of the Levenberg-Marquardt and Gauss algorithms for nonlinear least squares approximation. Numerische Mathematik, 18, 289-297.
3. BRUGGER, P., LANDIS, T., & REGARD, M. (1990). A "sheep-goat effect" in repetition avoidance: Extra sensory perception as an effect of subjective probability? British Journal of Psychology, 81, 455-468.
4. CHANDLER, J. P. (1969a). SIMPLEX - finds local minima of a function of several parameters. Behavioral Sciences, 14, 82.
5. CHANDLER, J. P. (1969b). STEPIT - finds local minima of a smooth function of several parameters. Behavioral Sciences, 14, 81.
6. COLLETT, D. (1991). Modelling binary data. London: Chapman & Hall.
7. CORSO, J. F. (1963). A theoretico-historical review of the threshold concept. Psychological Bulletin, 60, 356-370.
8. Cox, D. R., & SNELL, E. J. (1989). Analysis of binary data. London: Chapman & Hall.
9. EMERSON, P. L. (1986). A quadrature method for Bayesian sequential threshold estimation. Perception & Psychophysics, 39, 381-383.
10. RECHNER, G. T. (1965). Revision der Hauptpuncte der Psychophysik [Revision of the main topics of psychophysics]. Amsterdam: Bonset. (Original work published 1882)
11. FECHNER, G. T. (1966). In D. H. Howes & E. C. Boring (Eds.), and H. E. Adler (Trans.), Elements of psychophysics. Holt, Rinehart & Winston. (Original work published 1860)
12. FINNEY, D. J. (1971). Probit analysis. Cambridge: Cambridge University Press.
13. FISHER, R. A. (1912). On the absolute criterium for fitting frequency curves. Messenger of Mathematics, 41, 155-160.
14. FLETCHER, R. (1995). Practical methods of optimization. Chichester, U.K.: Wiley.
15. GARCÍA-PÉREZ, M. A. (1998). Forced-choice staircases: Some little known facts. Vision Research, 38, 1861-1881.
16. GREEN, D. M. (1990). Stimulus selection in adaptive psychophysical procedures. Journal of the Acoustical Society of America, 87, 2662-2674.
17. GREEN, D. M. (1993). A maximum-likelihood method for estimating thresholds in a yes-no task. Journal of the Acoustical Society of America, 87, 2096-2105.
18. GREEN, D. M., & SWETS, J. A. (1966). Signal detection theory and psychophysics. Los Altos, CA: Peninsula.
19. GUILFORD, J. P. (1954). Psychometric methods. New York: McGraw-Hill.
20. HALL, J. L. (1968). Maximum-likelihood sequential procedure for estimation of psychometric functions. Journal of the Acoustical Society of America, 44, 370.
21. HAMBLETON, R. K. (1989). Principles and selected applications of item response theory. In R. L. Linn (Ed.), Educational measurement (pp. 147-200). New York: Macmillan.
22. HAMBLETON, R. K., & SWAMINATHAN, H. (1985). Item response theory: Principles and applications. Boston: Kluwer Academic Publications.
23. HARVEY, L. O., JR. (1986). Efficient estimation of sensory thresholds. Behavior Research Methods, Instruments, & Computers, 18, 623-632.
24. HARVEY, L. O., JR. (1997). Efficient estimation of sensory thresholds with ML-PEST. Spatial Vision, 11, 121-128.
25. KAERNBACH, C. (1991). Simple adaptive testing with the weighted updown method. Perception & Psychophysics, 49, 227-229.
26. KESTEN, H. (1958). Accelerated stochastic approximation. Annals of Mathematical Statistics, 29, 41-59.
27. KING-SMITH, P. E., GRISBY, S.S., VINGRYS, A. J., BENES. S. C., & SUPOWIT, A. (1994). Comparison of the QUEST and related methods for measuring thresholds: Efficiency, bias and practical considerations. Vision Research, 34, 885-912.
28. KING-SMITH, P. E., & ROSE, D. (1997). Principles of an adaptive method for measuring the slope of the psychometric function. Vision Research, 37, 1595-1604.
29. LIEBERMAN, H. R., & PENTLAND, A. P. (1982). Microcomputer-based estimation of psychophysical thresholds: The Best PEST. Behavior Research Methods, Instruments, & Computers, 14, 21-25.
30. MACMILLAN, N. A., & CREELMAN, D. C. (1991). Detection theory: A users's guide. Cambridge: Cambridge University Press.
31. MADIGAN, R., & WILLIAMS, D. (1987). Maximum-likelihood psychometric procedures in two-alternative forced-choice: Evaluation and recommendations. Perception & Psychophysics, 42, 240-249.
32. MARTZ, H. F. & WALLER, R. A. (1982). Bayesian reliability analysis. New York: Wiley.
33. MCKEE, S. P., KLEIN, S. A., & TELLER, D. Y. (1985). Statistical properties of forced choice psychometric functions: Implications of probit analysis. Perception & Psychophysics, 37, 286-298.
34. MORGAN, B. J. T. (1992). Analysis of quantal response data. London: Chapman & Hall.
35. MÜLLER, G. E. (1879). Über die Maßbestimmungen des Ortssinnes der Haut mittelst der Methode der richtigen und falschen Fälle [On measuring the spatial sense of the skin with the method of right and wrong cases]. Pflügers Archiv, 19, 191-235.
36. NACHMIAS, J. (1981). On the psychometric function for contrast detection. Vision Research, 21, 215-223.
37. NELDER, J. A., & MEAD, R. (1965). A simplex method for function minimization. Computer Journal, 7, 308-313.
38. OLSSON, D. M., & NELSON, L. S. (1975). The nelder and mead simplex procedure for function minimization. Technometrics, 17, 45-51.
39. O'REGAN, J. K., & HUMBERT, R. (1989). Estimating psychometric functions in forced choice situations: Significant biases found in threshold and slope estimations when small samples are used. Perception & Psychophysics, 45, 434-442.
40. PRESS, W. H., TEUKOLSKY, S. A., VETTERLING, W. T., & FLANNERY, B. P. (1992). Numerical recipes in C: The art of scientific computing (2nd ed.). Cambridge: Cambridge University Press.
41. REICH, J. G. (1992). C curve fitting and modelling for scientists and engineers. New York: McGraw-Hill.
42. ROBBINS, H., & MONRO, S. (1951). A stochastic approximation method. Annals of Mathematical Statistics, 22, 400-407.
43. SWANSON, W. H., & BIRCH, E. E. (1992). Extracting thresholds from noisy psychophysical data. Perception & Psychophysics, 51, 409-422.
44. TREUTWEIN, B. (1995). Adaptive psychophysical procedures. Vision Research, 35, 2503-2522.
45. TREUTWEIN, B. (1997). YAAP: Yet another adaptive procedure. Spatial Vision, 11, 129-134.
46. TREUTWEIN, B., & RENTSCHLER, I. (1992). Double pulse resolution in the visual field: The influence of temporal stimulus characteristics. Clinical Vision Sciences, 1, 421-434.
47. TUKEY, J. W. (1977). Exploratory data analysis. Reading, MA: Addison-Wesley.
48. URBAN, F. M. (1908). The application of statistical methods to problems psychophysics. Philadelphia: Psychological Clinic Press.
49. WATSON, A. B. (1979). Probability summation over time. Vision Research, 19, 515-522.
50. WATSON, A. B., & PELLI, D. G. (1983). QUEST: A Bayesian adaptive psychometric method. Perception & Psychophysics, 33, 113-120.
51. WETHERILL, G. B. (1963). Sequential estimation of quantal response curves. Journal of the Royal Statistical Society, 25B, 1-48.