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

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.