Confidence intervals for the parameters of psychometric functions

Research output: Contribution to journalArticlepeer-review


A Monte Carlo method for computing the bias and standard deviation of estimates of the parameters of a psychometric function such as the Weibull/Quick is described. The method, based on Efron's parametric bootstrap, can also be used to estimate confidence intervals for these parameters. The method's ability to predict bias, standard deviation, and confidence intervals is evaluated in two ways. First, its predictions are compared to the outcomes of Monte Carlo simulations of psychophysical experiments. Second, its predicted confidence intervals were compared with the actual variability of human observers in a psychophysical task. Computer programs implementing the method are available from the author.

Original languageEnglish (US)
Pages (from-to)127-134
Number of pages8
JournalPerception & Psychophysics
Issue number2
StatePublished - Mar 1990

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • General Psychology
  • Sensory Systems


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