Stability and Change in Diffusion Model Parameters over Two Years
In recent years, mathematical models of decision making, such as the diffusion model, have been endorsed in individual differences research. These models can disentangle different components of the decision process, like processing speed, speed–accuracy trade-offs, and duration of non-decisional pro...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Journal of Intelligence |
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| Online Access: | https://www.mdpi.com/2079-3200/9/2/26 |
| _version_ | 1797534294181150720 |
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| author | Mischa von Krause Stefan T. Radev Andreas Voss Martin Quintus Boris Egloff Cornelia Wrzus |
| author_facet | Mischa von Krause Stefan T. Radev Andreas Voss Martin Quintus Boris Egloff Cornelia Wrzus |
| author_sort | Mischa von Krause |
| collection | DOAJ |
| description | In recent years, mathematical models of decision making, such as the diffusion model, have been endorsed in individual differences research. These models can disentangle different components of the decision process, like processing speed, speed–accuracy trade-offs, and duration of non-decisional processes. The diffusion model estimates individual parameters of cognitive process components, thus allowing the study of individual differences. These parameters are often assumed to show trait-like properties, that is, within-person stability across tasks and time. However, the assumption of temporal stability has so far been insufficiently investigated. With this work, we explore stability and change in diffusion model parameters by following over 270 participants across a time period of two years. We analysed four different aspects of stability and change: rank-order stability, mean-level change, individual differences in change, and profile stability. Diffusion model parameters showed strong rank-order stability and mean-level changes in processing speed and speed–accuracy trade-offs that could be attributed to practice effects. At the same time, people differed little in these patterns across time. In addition, profiles of individual diffusion model parameters proved to be stable over time. We discuss implications of these findings for the use of the diffusion model in individual differences research. |
| first_indexed | 2024-03-10T11:28:32Z |
| format | Article |
| id | doaj.art-2f6198664db543259e5d7a599b815f47 |
| institution | Directory Open Access Journal |
| issn | 2079-3200 |
| language | English |
| last_indexed | 2024-03-10T11:28:32Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Intelligence |
| spelling | doaj.art-2f6198664db543259e5d7a599b815f472023-11-21T19:27:28ZengMDPI AGJournal of Intelligence2079-32002021-05-01922610.3390/jintelligence9020026Stability and Change in Diffusion Model Parameters over Two YearsMischa von Krause0Stefan T. Radev1Andreas Voss2Martin Quintus3Boris Egloff4Cornelia Wrzus5Department of Psychology, Heidelberg University, 69117 Heidelberg, GermanyDepartment of Psychology, Heidelberg University, 69117 Heidelberg, GermanyDepartment of Psychology, Heidelberg University, 69117 Heidelberg, GermanyDepartment of Psychology, Mainz University, 55122 Mainz, GermanyDepartment of Psychology, Mainz University, 55122 Mainz, GermanyDepartment of Psychology, Heidelberg University, 69117 Heidelberg, GermanyIn recent years, mathematical models of decision making, such as the diffusion model, have been endorsed in individual differences research. These models can disentangle different components of the decision process, like processing speed, speed–accuracy trade-offs, and duration of non-decisional processes. The diffusion model estimates individual parameters of cognitive process components, thus allowing the study of individual differences. These parameters are often assumed to show trait-like properties, that is, within-person stability across tasks and time. However, the assumption of temporal stability has so far been insufficiently investigated. With this work, we explore stability and change in diffusion model parameters by following over 270 participants across a time period of two years. We analysed four different aspects of stability and change: rank-order stability, mean-level change, individual differences in change, and profile stability. Diffusion model parameters showed strong rank-order stability and mean-level changes in processing speed and speed–accuracy trade-offs that could be attributed to practice effects. At the same time, people differed little in these patterns across time. In addition, profiles of individual diffusion model parameters proved to be stable over time. We discuss implications of these findings for the use of the diffusion model in individual differences research.https://www.mdpi.com/2079-3200/9/2/26diffusion modelcognitive modellingindividual differencesstabilitylongitudinal study |
| spellingShingle | Mischa von Krause Stefan T. Radev Andreas Voss Martin Quintus Boris Egloff Cornelia Wrzus Stability and Change in Diffusion Model Parameters over Two Years Journal of Intelligence diffusion model cognitive modelling individual differences stability longitudinal study |
| title | Stability and Change in Diffusion Model Parameters over Two Years |
| title_full | Stability and Change in Diffusion Model Parameters over Two Years |
| title_fullStr | Stability and Change in Diffusion Model Parameters over Two Years |
| title_full_unstemmed | Stability and Change in Diffusion Model Parameters over Two Years |
| title_short | Stability and Change in Diffusion Model Parameters over Two Years |
| title_sort | stability and change in diffusion model parameters over two years |
| topic | diffusion model cognitive modelling individual differences stability longitudinal study |
| url | https://www.mdpi.com/2079-3200/9/2/26 |
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