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The diffusion model visualizer: an interactive tool to understand the diffusion model parameters
Response time (RT) data play an important role in psychology. The diffusion model (DM) allows to analyze RT-data in a two-alternative-force-choice paradigm using a particle drift diffusion modeling approach. It accounts for right-skewed distributions in a natural way. However, the model incorporates...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Berlin Heidelberg
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239816/ https://www.ncbi.nlm.nih.gov/pubmed/30361811 http://dx.doi.org/10.1007/s00426-018-1112-6 |
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author | Alexandrowicz, Rainer W. |
author_facet | Alexandrowicz, Rainer W. |
author_sort | Alexandrowicz, Rainer W. |
collection | PubMed |
description | Response time (RT) data play an important role in psychology. The diffusion model (DM) allows to analyze RT-data in a two-alternative-force-choice paradigm using a particle drift diffusion modeling approach. It accounts for right-skewed distributions in a natural way. However, the model incorporates seven parameters, the roles of which are difficult to comprehend from the model equation. Therefore, the present article introduces the diffusion model visualizer (DMV) allowing for interactive manipulation of each parameter and plotting the resulting RT densities. Thus, the DMV serves as a valuable tool for understanding the specific role of each model parameter. It may come in handy for didactical purposes and in research context. It allows for tracking down parameter estimation problems by delivering the model-based ideal densities, which can be juxtaposed to the data-based densities. It will also serve a valuable purpose in detecting outliers. The article describes the basics of the DM along with technical details of the DMV and gives several hints for its usage. |
format | Online Article Text |
id | pubmed-7239816 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-72398162020-05-27 The diffusion model visualizer: an interactive tool to understand the diffusion model parameters Alexandrowicz, Rainer W. Psychol Res Original Article Response time (RT) data play an important role in psychology. The diffusion model (DM) allows to analyze RT-data in a two-alternative-force-choice paradigm using a particle drift diffusion modeling approach. It accounts for right-skewed distributions in a natural way. However, the model incorporates seven parameters, the roles of which are difficult to comprehend from the model equation. Therefore, the present article introduces the diffusion model visualizer (DMV) allowing for interactive manipulation of each parameter and plotting the resulting RT densities. Thus, the DMV serves as a valuable tool for understanding the specific role of each model parameter. It may come in handy for didactical purposes and in research context. It allows for tracking down parameter estimation problems by delivering the model-based ideal densities, which can be juxtaposed to the data-based densities. It will also serve a valuable purpose in detecting outliers. The article describes the basics of the DM along with technical details of the DMV and gives several hints for its usage. Springer Berlin Heidelberg 2018-10-25 2020 /pmc/articles/PMC7239816/ /pubmed/30361811 http://dx.doi.org/10.1007/s00426-018-1112-6 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Alexandrowicz, Rainer W. The diffusion model visualizer: an interactive tool to understand the diffusion model parameters |
title | The diffusion model visualizer: an interactive tool to understand the diffusion model parameters |
title_full | The diffusion model visualizer: an interactive tool to understand the diffusion model parameters |
title_fullStr | The diffusion model visualizer: an interactive tool to understand the diffusion model parameters |
title_full_unstemmed | The diffusion model visualizer: an interactive tool to understand the diffusion model parameters |
title_short | The diffusion model visualizer: an interactive tool to understand the diffusion model parameters |
title_sort | diffusion model visualizer: an interactive tool to understand the diffusion model parameters |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239816/ https://www.ncbi.nlm.nih.gov/pubmed/30361811 http://dx.doi.org/10.1007/s00426-018-1112-6 |
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