QUEST+: A general multidimensional Bayesian adaptive psychometric method | Zendy

Andrew B. Watson | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

QUEST+: A general multidimensional Bayesian adaptive psychometric method

Author(s) -

Andrew B. Watson

Publication year - 2017

Publication title -

journal of vision

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.126

H-Index - 113

ISSN - 1534-7362

DOI - 10.1167/17.3.10

Subject(s) - psychometric function , computerized adaptive testing , bayesian probability , thurstone scale , computer science , categorical variable , psychophysics , parametric statistics , mathematics , statistics , perception , artificial intelligence , algorithm , psychometrics , psychology , neuroscience

QUEST+ is a Bayesian adaptive psychometric testing method that allows an arbitrary number of stimulus dimensions, psychometric function parameters, and trial outcomes. It is a generalization and extension of the original QUEST procedure and incorporates many subsequent developments in the area of parametric adaptive testing. With a single procedure, it is possible to implement a wide variety of experimental designs, including conventional threshold measurement; measurement of psychometric function parameters, such as slope and lapse; estimation of the contrast sensitivity function; measurement of increment threshold functions; measurement of noise-masking functions; Thurstone scale estimation using pair comparisons; and categorical ratings on linear and circular stimulus dimensions. QUEST+ provides a general method to accelerate data collection in many areas of cognitive and perceptual science.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research