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A MATLAB toolbox for the efficient estimation of the psychometric function using the updated maximum-likelihood adaptive procedure

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Abstract

A MATLAB toolbox for the efficient estimation of the threshold, slope, and lapse rate of the psychometric function is described. The toolbox enables the efficient implementation of the updated maximum-likelihood (UML) procedure. The toolbox uses an object-oriented architecture for organizing the experimental variables and computational algorithms, which provides experimenters with flexibility in experimental design and data management. Descriptions of the UML procedure and the UML Toolbox are provided, followed by toolbox use examples. Finally, guidelines and recommendations of parameter configurations are given.

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Notes

  1. A well-organized list of software available for the analysis of psychophysical functions, as well libraries/toolboxes for the collection of psychophysical data is available at http://visionscience.com/documents/strasburger/strasburger.html.

  2. Although the current toolbox was developed for the MATLAB environment, all source codes are contained in the toolbox and can be modified into other programing environments or languages.

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Author note

This work was supported by NIH NIDCD Grant No. R21 DC010058, awarded to the third author. We acknowledge Sierra N. Broussard’s assistance in running several computer simulations.

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Authors and Affiliations

  1. Department of Cognitive Sciences, University of California, 3151 Social Sciences Plaza, Irvine, CA, 92697-5100, USA

    Yi Shen & Virginia M. Richards

  2. Department of Computer Science, University of California, Irvine, CA, USA

    Wei Dai

Authors
  1. Yi Shen
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  2. Wei Dai
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  3. Virginia M. Richards
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Correspondence to Yi Shen.

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Shen, Y., Dai, W. & Richards, V.M. A MATLAB toolbox for the efficient estimation of the psychometric function using the updated maximum-likelihood adaptive procedure. Behav Res 47, 13–26 (2015). https://doi.org/10.3758/s13428-014-0450-6

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