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Bayesian Modeling of Cognitive Impairment in the Presence of Retest Effects

Diagnosing the early onset of neuropathologies, such as mild cognitive impairment (MCI), requires repeated evaluation of cognitive skills several times per year -- a measurement design known as a “burst design.” Detecting the often subtle cognitive decline in the presence of retest effects requires...

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Detalles Bibliográficos
Autores principales: Oravecz, Zita, Roque, Nelson, Sliwinski, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7741827/
http://dx.doi.org/10.1093/geroni/igaa057.1870
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author Oravecz, Zita
Roque, Nelson
Sliwinski, Martin
author_facet Oravecz, Zita
Roque, Nelson
Sliwinski, Martin
author_sort Oravecz, Zita
collection PubMed
description Diagnosing the early onset of neuropathologies, such as mild cognitive impairment (MCI), requires repeated evaluation of cognitive skills several times per year -- a measurement design known as a “burst design.” Detecting the often subtle cognitive decline in the presence of retest effects requires careful statistical modeling. The double exponential model offers a modeling framework to account for retest gains across measurement bursts, as well as warm-up effects within a burst, while quantifying change across bursts in peak performance. This talk highlights how a Bayesian multilevel implementation of the double exponential model allows for flexible extensions of this framework in terms of accommodating different timescales (nesting) and person-level predictors and drawing intuitive inferences on cognitive change with Bayesian posterior probabilities. We will use reaction time data to show how individual differences in asymptotic performance and change can be related to predictors such as age and MCI status. Part of a symposium sponsored by the Measurement, Statistics, and Research Design Interest Group.
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spelling pubmed-77418272020-12-21 Bayesian Modeling of Cognitive Impairment in the Presence of Retest Effects Oravecz, Zita Roque, Nelson Sliwinski, Martin Innov Aging Abstracts Diagnosing the early onset of neuropathologies, such as mild cognitive impairment (MCI), requires repeated evaluation of cognitive skills several times per year -- a measurement design known as a “burst design.” Detecting the often subtle cognitive decline in the presence of retest effects requires careful statistical modeling. The double exponential model offers a modeling framework to account for retest gains across measurement bursts, as well as warm-up effects within a burst, while quantifying change across bursts in peak performance. This talk highlights how a Bayesian multilevel implementation of the double exponential model allows for flexible extensions of this framework in terms of accommodating different timescales (nesting) and person-level predictors and drawing intuitive inferences on cognitive change with Bayesian posterior probabilities. We will use reaction time data to show how individual differences in asymptotic performance and change can be related to predictors such as age and MCI status. Part of a symposium sponsored by the Measurement, Statistics, and Research Design Interest Group. Oxford University Press 2020-12-16 /pmc/articles/PMC7741827/ http://dx.doi.org/10.1093/geroni/igaa057.1870 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstracts
Oravecz, Zita
Roque, Nelson
Sliwinski, Martin
Bayesian Modeling of Cognitive Impairment in the Presence of Retest Effects
title Bayesian Modeling of Cognitive Impairment in the Presence of Retest Effects
title_full Bayesian Modeling of Cognitive Impairment in the Presence of Retest Effects
title_fullStr Bayesian Modeling of Cognitive Impairment in the Presence of Retest Effects
title_full_unstemmed Bayesian Modeling of Cognitive Impairment in the Presence of Retest Effects
title_short Bayesian Modeling of Cognitive Impairment in the Presence of Retest Effects
title_sort bayesian modeling of cognitive impairment in the presence of retest effects
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7741827/
http://dx.doi.org/10.1093/geroni/igaa057.1870
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