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

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

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

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
Original languageEnglish
Pages (from-to)254-262
Number of pages9
JournalPERCEPTION & PSYCHOPHYSICS
Volume69
Publication statusPublished - 2007

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Sensory Systems
  • General Psychology

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