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Small-sample characterization of stochastic approximation staircases in forced-choice adaptive threshold estimation

Perception & Psychophysics volume 69, pages 254–262 (2007)Cite this article

Abstract

Despite the widespread use of up—down staircases in adaptive threshold estimation, their efficiency and usability in forced-choice experiments has been recently debated. In this study, simulation techniques were used to determine the small-sample convergence properties of stochastic approximation (SA) staircases as a function of several experimental parameters. We found that satisfying some general requirements (use of the accelerated SA algorithm, clear suprathreshold initial stimulus intensity, large initial step size) the convergence was accurate independently of the spread of the underlying psychometric function. SA staircases were also reliable for targeting percent-correct levels far from the midpoint of the psychometric function and performed better than classical up—down staircases with fixed step size. These results prompt the utilization of SA staircases in practical forced-choice estimation of sensory thresholds.

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Affiliations

  1. Lab. Biosegnali, Dipartimento di Fisica, Università di Trento, via Sommarive 14, 38050, Povo, Trento, Italy

    Luca Faes, Giandomenico Nollo, Flavia Ravelli, Leonardo Ricci, Massimo Vescovi, Massimo Turatto, Francesco Pavani & Renzo Antolini

  2. ITC, Trento, Italy

    Giandomenico Nollo & Flavia Ravelli

Authors
  1. Luca Faes
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  2. Giandomenico Nollo
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  3. Flavia Ravelli
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  4. Leonardo Ricci
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  5. Massimo Vescovi
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  6. Massimo Turatto
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  7. Francesco Pavani
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  8. Renzo Antolini
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Correspondence to Luca Faes.

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Faes, L., Nollo, G., Ravelli, F. et al. Small-sample characterization of stochastic approximation staircases in forced-choice adaptive threshold estimation. Perception & Psychophysics 69, 254–262 (2007). https://doi.org/10.3758/BF03193747

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  • DOI: https://doi.org/10.3758/BF03193747

Keywords

  • Stimulus Intensity
  • Psychometric Function
  • Stochastic Approximation
  • Target Probability
  • Stimulus Level