Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences

Growth curve studies are typically conducted to evaluate differences between group or treatment-specific curves. Most analyses focus solely on the growth curves, but it has been argued that the derivative of growth curves can highlight differences between groups that may be masked when considering t...

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Detalhes bibliográficos
Autores: Page, G.L., Rodríguez-Álvarez, M.X., Lee, D.J.
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2020
País:España
Recursos:Basque Center for Applied Mathematics (BCAM)
Repositorio:BIRD. BCAM's Institutional Repository Data
OAI Identifier:oai:bird.bcamath.org:20.500.11824/1097
Acesso em linha:http://hdl.handle.net/20.500.11824/1097
Access Level:acceso embargado
Palavra-chave:Bayesian hierarchical models
Growth studies
Longitudinal data
Penalized splines
Smoothing
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spelling Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differencesPage, G.L.Rodríguez-Álvarez, M.X.Lee, D.J.Bayesian hierarchical modelsGrowth studiesLongitudinal dataPenalized splinesSmoothingGrowth curve studies are typically conducted to evaluate differences between group or treatment-specific curves. Most analyses focus solely on the growth curves, but it has been argued that the derivative of growth curves can highlight differences between groups that may be masked when considering the raw curves only. Motivated by the desire to estimate derivative curves hierarchically, we introduce a new sequence of quotient differences (empirical derivatives) which, among other things, are well behaved near the boundaries compared with other sequences in the literature. Using the sequence of quotient differences, we develop a Bayesian method to estimate curve derivatives in a multilevel setting (a common scenario in growth studies) and show ow the method can be used to estimate individual and group derivative curves and to make comparisons. We apply the new methodology to data collected from a study conducted to explore the effect that radiation-based therapies have on growth in female children diagnosed with acute lymphoblastic leukaemia.info202020202020info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttp://hdl.handle.net/20.500.11824/1097reponame:BIRD. BCAM's Institutional Repository Datainstname:Basque Center for Applied Mathematics (BCAM)Ingléshttps://rss.onlinelibrary.wiley.com/doi/abs/10.1111/rssc.12399info:eu-repo/grantAgreement/MINECO//SEV-2017-0718info:eu-repo/grantAgreement/MINECO//MTM2017-82379-Rinfo:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2018-2021Reconocimiento-NoComercial-CompartirIgual 3.0 Españahttp://creativecommons.org/licenses/by-nc-sa/3.0/es/info:eu-repo/semantics/embargoedAccessoai:bird.bcamath.org:20.500.11824/10972026-06-19T12:47:47Z
dc.title.none.fl_str_mv Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences
title Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences
spellingShingle Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences
Page, G.L.
Bayesian hierarchical models
Growth studies
Longitudinal data
Penalized splines
Smoothing
title_short Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences
title_full Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences
title_fullStr Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences
title_full_unstemmed Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences
title_sort Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences
dc.creator.none.fl_str_mv Page, G.L.
Rodríguez-Álvarez, M.X.
Lee, D.J.
author Page, G.L.
author_facet Page, G.L.
Rodríguez-Álvarez, M.X.
Lee, D.J.
author_role author
author2 Rodríguez-Álvarez, M.X.
Lee, D.J.
author2_role author
author
dc.subject.none.fl_str_mv Bayesian hierarchical models
Growth studies
Longitudinal data
Penalized splines
Smoothing
topic Bayesian hierarchical models
Growth studies
Longitudinal data
Penalized splines
Smoothing
description Growth curve studies are typically conducted to evaluate differences between group or treatment-specific curves. Most analyses focus solely on the growth curves, but it has been argued that the derivative of growth curves can highlight differences between groups that may be masked when considering the raw curves only. Motivated by the desire to estimate derivative curves hierarchically, we introduce a new sequence of quotient differences (empirical derivatives) which, among other things, are well behaved near the boundaries compared with other sequences in the literature. Using the sequence of quotient differences, we develop a Bayesian method to estimate curve derivatives in a multilevel setting (a common scenario in growth studies) and show ow the method can be used to estimate individual and group derivative curves and to make comparisons. We apply the new methodology to data collected from a study conducted to explore the effect that radiation-based therapies have on growth in female children diagnosed with acute lymphoblastic leukaemia.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020
2020
info
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.11824/1097
url http://hdl.handle.net/20.500.11824/1097
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://rss.onlinelibrary.wiley.com/doi/abs/10.1111/rssc.12399
info:eu-repo/grantAgreement/MINECO//SEV-2017-0718
info:eu-repo/grantAgreement/MINECO//MTM2017-82379-R
info:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2018-2021
dc.rights.none.fl_str_mv Reconocimiento-NoComercial-CompartirIgual 3.0 España
http://creativecommons.org/licenses/by-nc-sa/3.0/es/
info:eu-repo/semantics/embargoedAccess
rights_invalid_str_mv Reconocimiento-NoComercial-CompartirIgual 3.0 España
http://creativecommons.org/licenses/by-nc-sa/3.0/es/
eu_rights_str_mv embargoedAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:BIRD. BCAM's Institutional Repository Data
instname:Basque Center for Applied Mathematics (BCAM)
instname_str Basque Center for Applied Mathematics (BCAM)
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