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jsQuestPlus: A JavaScript implementation of the QUEST+ method for estimating psychometric function parameters in

Daiichiro Kuroki1, Thomas Pronk2

  • 1Department of Psychology, School of Letters, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka, 819-0395, Japan. kurokid@kyudai.jp.

Behavior Research Methods
|September 7, 2022
PubMed
Summary

jsQuestPlus is a new JavaScript library enabling online use of the QUEST+ method for psychometric parameter estimation. It is fast, accurate, and integrates with popular online experiment tools.

Keywords:
Adaptive psychometric methodsOnline experimentsPsychometric functionsPsychophysical threshold

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Area of Science:

  • Psychophysics
  • Computational Psychology
  • Human-Computer Interaction

Background:

  • Bayesian adaptive psychometric methods like QUEST and QUEST+ are standard for laboratory experiments.
  • The rise of online psychophysical experiments necessitates web-based implementations of these methods.

Purpose of the Study:

  • To introduce jsQuestPlus, a JavaScript library for the QUEST+ psychometric method.
  • To evaluate the performance and accuracy of jsQuestPlus for online psychophysical studies.

Main Methods:

  • Development of a JavaScript library, jsQuestPlus, for the QUEST+ algorithm.
  • Integration of jsQuestPlus with online experimental platforms (jsPsych, PsychoPy/JS, lab.js).
  • Performance evaluation through computation time measurements and accuracy comparisons across various browser-computer combinations.

Main Results:

  • jsQuestPlus demonstrated efficient performance with mean initialization time of 461.08 ms and update time of 79.39 ms.
  • Stimulus parameter computation time was consistently under 1 ms.
  • Estimated psychometric parameters showed accuracy comparable to the original QUEST+ method.

Conclusions:

  • jsQuestPlus is a computationally efficient and accurate tool for conducting online psychophysical experiments.
  • The library overcomes the complexities of matrix calculations for web-based applications.
  • jsQuestPlus is freely available under the MIT license for broader research use.