Jumping to Conclusion? A Lévy Flight Model of Decision Making [Dataset] (doi:10.11588/data/SXWI6S)

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Document Description

Citation

Title:

Jumping to Conclusion? A Lévy Flight Model of Decision Making [Dataset]

Identification Number:

doi:10.11588/data/SXWI6S

Distributor:

heiDATA

Date of Distribution:

2021-02-10

Version:

1

Bibliographic Citation:

Wieschen, Eva Marie; Voss, Andreas; Radev, Stefan, 2021, "Jumping to Conclusion? A Lévy Flight Model of Decision Making [Dataset]", https://doi.org/10.11588/data/SXWI6S, heiDATA, V1

Study Description

Citation

Title:

Jumping to Conclusion? A Lévy Flight Model of Decision Making [Dataset]

Identification Number:

doi:10.11588/data/SXWI6S

Authoring Entity:

Wieschen, Eva Marie (Institute of Psychology)

Voss, Andreas (Institute of Psychology)

Radev, Stefan (Institute of Psychology)

Grant Number:

GRK 2277

Distributor:

heiDATA

Access Authority:

Voss, Andreas

Date of Deposit:

2021-02-09

Holdings Information:

https://doi.org/10.11588/data/SXWI6S

Study Scope

Keywords:

Social Sciences, Lévy flights, diffusion model, decision making

Abstract:

The diffusion model is one of the most prominent response time models in cognitive psychology. The model describes evidence accumulation as a stochastic process that runs between two boundaries until a threshold is hit, and a decision is made. The model assumes that information accumulation follows a Wiener diffusion process with normally distributed noise. However, the model's assumption of Gaussian noise might not be the optimal description of decision making. We argue that Lévy flights, incorporating more heavy-tailed, non-Gaussian noise, might provide a more accurate description of actual decision processes. In contrast to diffusion processes, Lévy flights are characterized by larger jumps in the decision process. To further examine this proposal, we compare the fit of the basic diffusion model and the full diffusion model (including inter-trial variability of starting-point, drift rate and non-decisional processes) to the fit of a simple and a complex version of a Lévy flight model. In the latter model, the heavy-tailedness of noise distributions was estimated by an additional free stability parameter alpha. Participants completed 500 trials of a color discrimination task and 400 trials of a lexical decision task. Results indicate that a complex Lévy flight model -including inter-trial variability parameters and alpha- shows the best fit in both tasks. Importantly, alpha-values correlated across tasks, indicating a trait-like nature of this parameter.

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Related Publications

Citation

Title:

Wieschen, Eva Marie, Voss, Andreas, Radev, Stefan (2020) Jumping to Conclusion? A Lévy Flight Model of Decision Making, The Quantitative Methods for Psychology, 16(2), 120-132.

Identification Number:

10.20982/tqmp.16.2.p120

Bibliographic Citation:

Wieschen, Eva Marie, Voss, Andreas, Radev, Stefan (2020) Jumping to Conclusion? A Lévy Flight Model of Decision Making, The Quantitative Methods for Psychology, 16(2), 120-132.

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