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Bivariate joint models for survival and change of cognitive function

Changes in cognitive function over time are of interest in ageing research. A joint model is constructed to investigate. Generally, cognitive function is measured through more than one test, and the test scores are integers. The aim is to investigate two test scores and use an extension of a bivaria...

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Autores principales: Pan, Shengning, van den Hout, Ardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9983056/
https://www.ncbi.nlm.nih.gov/pubmed/36573012
http://dx.doi.org/10.1177/09622802221146307
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author Pan, Shengning
van den Hout, Ardo
author_facet Pan, Shengning
van den Hout, Ardo
author_sort Pan, Shengning
collection PubMed
description Changes in cognitive function over time are of interest in ageing research. A joint model is constructed to investigate. Generally, cognitive function is measured through more than one test, and the test scores are integers. The aim is to investigate two test scores and use an extension of a bivariate binomial distribution to define a new joint model. This bivariate distribution model the correlation between the two test scores. To deal with attrition due to death, the Weibull hazard model and the Gompertz hazard model are used. A shared random-effects model is constructed, and the random effects are assumed to follow a bivariate normal distribution. It is shown how to incorporate random effects that link the bivariate longitudinal model and the survival model. The joint model is applied to the English Longitudinal Study of Ageing data.
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spelling pubmed-99830562023-03-04 Bivariate joint models for survival and change of cognitive function Pan, Shengning van den Hout, Ardo Stat Methods Med Res Original Research Articles Changes in cognitive function over time are of interest in ageing research. A joint model is constructed to investigate. Generally, cognitive function is measured through more than one test, and the test scores are integers. The aim is to investigate two test scores and use an extension of a bivariate binomial distribution to define a new joint model. This bivariate distribution model the correlation between the two test scores. To deal with attrition due to death, the Weibull hazard model and the Gompertz hazard model are used. A shared random-effects model is constructed, and the random effects are assumed to follow a bivariate normal distribution. It is shown how to incorporate random effects that link the bivariate longitudinal model and the survival model. The joint model is applied to the English Longitudinal Study of Ageing data. SAGE Publications 2022-12-26 2023-03 /pmc/articles/PMC9983056/ /pubmed/36573012 http://dx.doi.org/10.1177/09622802221146307 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research Articles
Pan, Shengning
van den Hout, Ardo
Bivariate joint models for survival and change of cognitive function
title Bivariate joint models for survival and change of cognitive function
title_full Bivariate joint models for survival and change of cognitive function
title_fullStr Bivariate joint models for survival and change of cognitive function
title_full_unstemmed Bivariate joint models for survival and change of cognitive function
title_short Bivariate joint models for survival and change of cognitive function
title_sort bivariate joint models for survival and change of cognitive function
topic Original Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9983056/
https://www.ncbi.nlm.nih.gov/pubmed/36573012
http://dx.doi.org/10.1177/09622802221146307
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