Literature DB >> 18183889

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

Andreas Voss1, Jochen Voss.   

Abstract

In the present article, a flexible and fast computer program, called fast-dm, for diffusion model data analysis is introduced. Fast-dm is free software that can be downloaded from the authors' websites. The program allows estimating all parameters of Ratcliff's (1978) diffusion model from the empirical response time distributions of any binary classification task. Fast-dm is easy to use: it reads input data from simple text files, while program settings are specified by commands in a control file. With fast-dm, complex models can be fitted, where some parameters may vary between experimental conditions, while other parameters are constrained to be equal across conditions. Detailed directions for use of fast-dm are presented, as well as results from three short simulation studies exemplifying the utility of fast-dm.

Mesh:

Year:  2007        PMID: 18183889     DOI: 10.3758/bf03192967

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  96 in total

1.  Fitting the Ratcliff diffusion model to experimental data.

Authors:  Joachm Vandekerckhove; Francis Tuerlinckx
Journal:  Psychon Bull Rev       Date:  2007-12

2.  Comparing time-accuracy curves: beyond goodness-of-fit measures.

Authors:  Charles C Liu; Philip L Smith
Journal:  Psychon Bull Rev       Date:  2009-02

3.  EZ does it! Extensions of the EZ-diffusion model.

Authors:  Eric-Jan Wagenmakers; Han L J van der Maas; Conor V Dolan; Raoul P P P Grasman
Journal:  Psychon Bull Rev       Date:  2008-12

4.  The overconstraint of response time models: rethinking the scaling problem.

Authors:  Chris Donkin; Scott D Brown; Andrew Heathcote
Journal:  Psychon Bull Rev       Date:  2009-12

5.  A diffusion model decomposition of the practice effect.

Authors:  Gilles Dutilh; Joachim Vandekerckhove; Francis Tuerlinckx; Eric-Jan Wagenmakers
Journal:  Psychon Bull Rev       Date:  2009-12

6.  A diffusion model analysis of task interference effects in prospective memory.

Authors:  C Dennis Boywitt; Jan Rummel
Journal:  Mem Cognit       Date:  2012-01

7.  Electrophysiological correlates of the drift diffusion model in visual word recognition.

Authors:  Christina J Mueller; Corey N White; Lars Kuchinke
Journal:  Hum Brain Mapp       Date:  2017-07-31       Impact factor: 5.038

8.  Increased cognitive control after task conflict? Investigating the N-3 effect in task switching.

Authors:  Stefanie Schuch; James A Grange
Journal:  Psychol Res       Date:  2018-05-25

9.  People adopt optimal policies in simple decision-making, after practice and guidance.

Authors:  Nathan J Evans; Scott D Brown
Journal:  Psychon Bull Rev       Date:  2017-04

Review 10.  Diffusion Decision Model: Current Issues and History.

Authors:  Roger Ratcliff; Philip L Smith; Scott D Brown; Gail McKoon
Journal:  Trends Cogn Sci       Date:  2016-03-05       Impact factor: 20.229

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