Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Fast-dm: a free program for efficient diffusion model analysis.

Andreas Voss1, Jochen Voss

  • 1Institut für Psychologie, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany. voss@psychologie.uni-freiburg.de

Behavior Research Methods
|January 11, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Alexander view as a stand-alone alternative to standard anteroposterior imaging for treatment decisions in acute acromioclavicular joint dislocation.

JSES international·2026
Same author

Environmental cleaning and disinfection practices for respiratory viruses in hospitals and long-term care facilities in the Netherlands.

Antimicrobial resistance and infection control·2026
Same author

Erratum: Multivariate assessment of the central-cardiorespiratory network structure in neuropathological disease (2018<i>Physiol. Meas</i>.<b>39</b>074004).

Physiological measurement·2026
Same author

Nosocomial outbreaks with rare yeasts: Trends, characteristics and preventive measures.

The Journal of infection·2026
Same author

Cognitive processes underlying the repetition-based truth effect: A diffusion model study.

Journal of experimental psychology. Learning, memory, and cognition·2026
Same author

How many infection control staff members are needed in acute care hospitals? A Delphi approach.

The Journal of hospital infection·2026
Same journal

Exploring psychological tradeoffs: Developing and demonstrating an R Shiny app for Pareto optimization.

Behavior research methods·2026
Same journal

The performance of Bayesian fit measures in detecting misspecified multilevel structural equation modeling.

Behavior research methods·2026
Same journal

Psychometric functions from multiple responses : Dedicated to the memory of Colin L. Mallows.

Behavior research methods·2026
Same journal

Low-cost, open-source, full-stack software and Arduino-based hardware for control of commercially available animal behavior systems.

Behavior research methods·2026
Same journal

PyNeon: A Python package for the analysis of Neon multimodal mobile eye-tracking data.

Behavior research methods·2026
Same journal

Talking surveys: How photorealistic embodied conversational agents shape response quality, engagement, and satisfaction.

Behavior research methods·2026
See all related articles

A new free software, fast-dm, enables flexible analysis of diffusion model data. This tool accurately estimates parameters from response time distributions for binary classification tasks.

Area of Science:

  • Cognitive psychology
  • Computational neuroscience
  • Psychometric modeling

Background:

  • Diffusion models are crucial for understanding decision-making.
  • Estimating diffusion model parameters from response time data can be complex.
  • Existing software may lack flexibility or ease of use.

Purpose of the Study:

  • Introduce fast-dm, a novel, free software for diffusion model data analysis.
  • Provide a user-friendly tool for estimating Ratcliff's diffusion model parameters.
  • Demonstrate the software's capability in fitting complex, condition-specific models.

Main Methods:

  • Developed fast-dm as a flexible and fast computer program.
  • Utilized empirical response time distributions from binary classification tasks.

Related Experiment Videos

  • Implemented parameter estimation for Ratcliff's (1978) diffusion model.
  • Designed for ease of use with text file input and control file settings.

    • Main Results:

    • fast-dm successfully estimates all parameters of Ratcliff's diffusion model.
    • The software handles complex model fitting with varying and constrained parameters across conditions.
    • Simulation studies confirm the utility and accuracy of fast-dm.

    Conclusions:

    • fast-dm offers a powerful and accessible solution for diffusion model analysis.
    • The software facilitates advanced modeling of decision-making processes.
    • Researchers can readily apply fast-dm to their binary classification tasks.