Psychometric Function Modeling

Psychometric Function Modeling is a statistical modeling approach that characterizes the relationship between a physical stimulus intensity and an observer's behavioral response probability, specifically by specifying the functional form, parameters, and error structure that describe the sigmoidal transition from chance to maximal performance in a perceptual or cognitive task.

214

Publications

20.2K

Citations

465

Authors

242

Institutions

Publications per year

2017–2026

33

Authors

465

  1. MA
    Miguel A. García‐Pérez

    Universidad Complutense de Madrid, Spain

    8 publications · 321 citations

    8

    h-index

  2. DM
    David M. Green

    McGill University, Canada

    7 publications · 462 citations

    7

    h-index

  3. RA
    Rocío Alcalá‐Quintana

    Universidad Complutense de Madrid, Spain

    6 publications · 227 citations

    6

    h-index

  4. FA
    Felix A. Wichmann

    Max Planck Institute for Biological Cybernetics, Germany

    4 publications · 936 citations

    4

    h-index

  5. JR
    Judy R. Dubno

    Medical University of South Carolina, United States

    4 publications · 108 citations

    4

    h-index

1–5 of 465

Venues

  1. The Journal of the Acoustical Society of America

    JASA · 35 publications · 1.9K citations

    23

    h-index

  2. Journal of Vision

    21 publications · 2.3K citations

    17

    h-index

  3. Vision Research

    9 publications · 1.4K citations

    9

    h-index

  4. Perception & Psychophysics

    7 publications · 427 citations

    7

    h-index

  5. Psychological Review

    6 publications · 332 citations

    6

    h-index

1–5