Literature DB >> 31062193

DstarM: an R package for analyzing two-choice reaction time data with the D∗M method.

Don van den Bergh1,2, Francis Tuerlinckx3, Stijn Verdonck3.   

Abstract

The decision process in choice reaction time data is traditionally described in detail with diffusion models. However, the total reaction time is assumed to consist of the sum of a decision time (as modeled by the diffusion process) and the time devoted to nondecision processes (e.g., perceptual and motor processes). It has become standard practice to assume that the nondecision time is uniformly distributed. However, a misspecification of the nondecision time distribution introduces bias in the parameter estimates for the decision model. Recently, a new method has been proposed (called the D∗M method) that allows the estimation of the decision model parameters, while leaving the nondecision time distribution unspecified. In a second step, a nonparametric estimate of the nondecision time distribution may be retrieved. In this paper, we present an R package that estimates parameters of several diffusion models via the D∗M method. Moreover, it is shown in a series of extensive simulation studies that the parameters of the decision model and the nondecision distributions are correctly retrieved.

Entities:  

Keywords:  Choice response time; Diffusion models; D∗M

Year:  2020        PMID: 31062193      PMCID: PMC7148288          DOI: 10.3758/s13428-019-01249-7

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


  8 in total

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

Authors:  Roger Ratcliff; Francis Tuerlinckx
Journal:  Psychon Bull Rev       Date:  2002-09

2.  A diffusion model account of the lexical decision task.

Authors:  Roger Ratcliff; Pablo Gomez; Gail McKoon
Journal:  Psychol Rev       Date:  2004-01       Impact factor: 8.934

3.  Factoring out nondecision time in choice reaction time data: Theory and implications.

Authors:  Stijn Verdonck; Francis Tuerlinckx
Journal:  Psychol Rev       Date:  2015-12-07       Impact factor: 8.934

Review 4.  The diffusion decision model: theory and data for two-choice decision tasks.

Authors:  Roger Ratcliff; Gail McKoon
Journal:  Neural Comput       Date:  2008-04       Impact factor: 2.026

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

Authors:  Andreas Voss; Jochen Voss
Journal:  Behav Res Methods       Date:  2007-11

6.  A Diffusion Model Account of Criterion Shifts in the Lexical Decision Task.

Authors:  Eric-Jan Wagenmakers; Roger Ratcliff; Pablo Gomez; Gail McKoon
Journal:  J Mem Lang       Date:  2008-01       Impact factor: 3.059

7.  Parameter variability and distributional assumptions in the diffusion model.

Authors:  Roger Ratcliff
Journal:  Psychol Rev       Date:  2012-11-12       Impact factor: 8.934

Review 8.  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

  8 in total

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