Psychonomic Bulletin & Review

, Volume 15, Issue 6, pp 1201–1208

A hierarchical approach for fitting curves to response time measurements

  • Jeffrey N. Rouder
  • Francis Tuerlinckx
  • Paul Speckman
  • Jun Lu
  • Pablo Gomez
Notes and Comment

DOI: 10.3758/PBR.15.6.1201

Cite this article as:
Rouder, J.N., Tuerlinckx, F., Speckman, P. et al. Psychonomic Bulletin & Review (2008) 15: 1201. doi:10.3758/PBR.15.6.1201
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Abstract

Understanding how response time (RT) changes with manipulations has been critical in distinguishing among theories in cognition. It is well known that aggregating data distorts functional relationships (e.g., Estes, 1956). Less well appreciated is a second pitfall: Minimizing squared errors (i.e., OLS regression) also distorts estimated functional forms with RT data. We discuss three properties of RT that should be modeled for accurate analysis and, on the basis of these three properties, provide a hierarchical Weibull regression model for regressing RT onto covariates. Hierarchical regression model analysis of lexical decision task data reveals that RT decreases as a power function of word frequency with the scale of RT decreasing 11% for every doubling of word frequency. A detailed discussion of the model and analysis techniques are presented as archived materials and may be downloaded from www.psychonomic.org/archive.

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Copyright information

© Psychonomic Society, Inc. 2008

Authors and Affiliations

  • Jeffrey N. Rouder
    • 4
  • Francis Tuerlinckx
    • 1
  • Paul Speckman
    • 4
  • Jun Lu
    • 2
  • Pablo Gomez
    • 3
  1. 1.University of LeuvenLeuvenBelgium
  2. 2.American UniversityWashington, DC
  3. 3.DePaul UniversityChicago
  4. 4.Department of Psychological SciencesUniversity of MissouriColumbia