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Cited by 838Decision-Making and Behavioral EconomicsPsychometric Methodologies and TestingNeural and Behavioral Psychology Studies

Estimating parameters of the diffusion model: Approaches to dealing with contaminant reaction times and parameter variability

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Ratcliff, Roger, Tuerlinckx, Francis·2002·Psychonomic Bulletin & Review
DOI 10.3758/bf03196302PMC PMC2474747
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Abstract

Three methods for fitting the diffusion model (Ratcliff, 1978) to experimental data are examined. Sets of simulated data were generated with known parameter values, and from fits of the model, we found that the maximum likelihood method was better than the chi-square and weighted least squares methods by criteria of bias in the parameters relative to the parameter values used to generate the data and standard deviations in the parameter estimates. The standard deviations in the parameter values can be used as measures of the variability in parameter estimates from fits to experimental data. We introduced contaminant reaction times and variability into the other components of processing besides the decision process and found that the maximum likelihood and chi-square methods failed, sometimes dramatically. But the weighted least squares method was robust to these two factors. We then present results from modifications of the maximum likelihood and chi-square methods, in which these factors are explicitly modeled, and show that the parameter values of the diffusion model are recovered well. We argue that explicit modeling is an important method for addressing contaminants and variability in nondecision processes and that it can be applied in any theoretical approach to modeling reaction time.

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  • The 0.3 s cutoff was chosen as a conservative threshold for fast outliers based on best practices in the drift diffusion modeling literature.

    “The 0.3 s cutoff was chosen as a conservative threshold for fast outliers based on best practices in the drift diffusion modeling literature 49 , and also given that even the simplest perceptual discrimination decisions are rarely made faster than 0.3 s.”

    From Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions (2019) · cites this paper as [49]

    In “Contaminant Reaction Times” (page not provided), the paper uses 300 msec as an example of an initial cutoff for examining fast responses. It then recommends raising the cutoff and checking accuracy to determine an appropriate value; it does not establish 0.3 s as a generally conservative fixed threshold. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • The 5 s cutoff was chosen as a conservative threshold for slow outliers based on DDM characterization for relatively fast decisions of 1-1.5s.

    “Similarly, given that DDMs have been best characterized for relatively fast decisions of 1–1.5s 37 , we chose to threshold slow outliers at a conservative cutoff of 5 s, which excluded a small number of trials 49 .”

    From Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions (2019) · cites this paper as [49]

    In “The Diffusion Model” (page unavailable), the paper says diffusion models best apply to two-choice decisions whose reaction times do not average much over 1 second. In “Contaminant Reaction Times” (page unavailable), it recommends setting a slow-outlier cutoff above which few responses fall, depending on the research goal. It does not specify a 5-second cutoff or derive one from the model’s usual decision times; the citing authors’ choice of 5 seconds is their own. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 4

  1. Audley, R. J., & Pike, A. R. (1965). Some alternative stochastic mod- els of choice. British Journal of Mathematical & Statistical Psychol- ogy, 18, 207-225.
  2. Gill, P. E., Murray, W., Saunders, M. A., & Wright, M. H. (1998). User's guide for NPSOL 5.0: A Fortran package for nonlinear pro- gramming (Tech. Rep. SOL 86-1). Stanford: Stanford University, Sys- tems Optimization Laboratory.
  3. Jeffreys, H. (1961). Theory of probability (3rd ed.). Oxford: Oxford University Press.
  4. Link, S. W. (1975). The relative judgement theory of two choice re- sponse time. Journal of Mathematical Psychology, 12, 114-135.

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Authors
Ratcliff, R., & Tuerlinckx, F.
Affiliations
  • Northwestern University (US)
  • KU Leuven (BE)
Corresponding author
Ratcliff, Roger
ORCID
Venue
Psychonomic Bulletin & Review
Publisher
Springer Science and Business Media LLC
Published
2002-09
Volume
9
Issue
3
Pages
438-481
ISSN
  • 1069-9384 (ISSN-L)
  • 1531-5320
DOI
10.3758/bf03196302
PMC
PMC2474747
OpenAlex
W2006388199
Cited by
838
References
71
Citations by year
2026: 34 · 2025: 39 · 2024: 51 · 2023: 53 · 2022: 51 · 2021: 44 · 2020: 56 · 2019: 58 · 2018: 62 · 2017: 38 · 2016: 50 · 2015: 44 · 2014: 39 · 2013: 23 · 2012: 30
FWCI
7.82
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Psychonomic Bulletin & Review (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • Lirias (KU Leuven) (submittedVersion, other-oa)
Funders
  • National Institute on Aging (AG17083, R01AG017083, R01 AG17083)
  • National Institute of Mental Health (R37MH044640, MH01891, K05MH001891, R37 MH 44640, MH 44640, K05 MH 01891)
  • National Institute on Deafness and Other Communication Disorders (R01 DC 01240, R01DC001240)
Topics
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Keywords
diffusion models, parameter estimation, maximum likelihood estimation, chi-square fitting, weighted least squares, parameter variation
MeSH terms
Humans, Reaction Time, Models, Statistical

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