Quantile maximum likelihood estimation of response time distributions

Psychon Bull Rev. 2002 Jun;9(2):394-401. doi: 10.3758/bf03196299.


We introduce and evaluate via a Monte Carlo study a robust new estimation technique that fits distribution functions to grouped response time (RT) data, where the grouping is determined by sample quantiles. The new estimator, quantile maximum likelihood (QML), is more efficient and less biased than the best alternative estimation technique when fitting the commonly used ex-Gaussian distribution. Limitations of the Monte Carlo results are discussed and guidance provided for the practical application of the new technique. Because QML estimation can be computationally costly, we make fast open source code for fitting available that can be easily modified to use QML in the estimation of any distribution function.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Interpretation, Statistical
  • Humans
  • Likelihood Functions*
  • Monte Carlo Method
  • Normal Distribution
  • Reaction Time*
  • Reproducibility of Results