survidm: An R package for Inference and Prediction in an Illness-Death Model
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/79140 |
Resumo: | Multi-state models are a useful way of describing a process in which an individual moves through a number of finite states in continuous time. The illness-death model plays a central role in the theory and practice of these models, describing the dynamics of healthy subjects who may move to an intermediate "diseased" state before entering into a terminal absorbing state. In these models, one important goal is the modeling of transition rates which is usually done by studying the relationship between covariates and disease evolution. However, biomedical researchers are also interested in reporting other interpretable results in a simple and summarized manner. These include estimates of predictive probabilities, such as the transition probabilities, occupation probabilities, cumulative incidence functions, and the sojourn time distributions. The development of survidm package has been motivated by recent contribution that provides answers to all these topics. An illustration of the software usage is included using real data. |
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survidm: An R package for Inference and Prediction in an Illness-Death Modelmultistate modelillness-deathmultistate regressiontransition probabilitiesCiências Naturais::MatemáticasScience & TechnologyMulti-state models are a useful way of describing a process in which an individual moves through a number of finite states in continuous time. The illness-death model plays a central role in the theory and practice of these models, describing the dynamics of healthy subjects who may move to an intermediate "diseased" state before entering into a terminal absorbing state. In these models, one important goal is the modeling of transition rates which is usually done by studying the relationship between covariates and disease evolution. However, biomedical researchers are also interested in reporting other interpretable results in a simple and summarized manner. These include estimates of predictive probabilities, such as the transition probabilities, occupation probabilities, cumulative incidence functions, and the sojourn time distributions. The development of survidm package has been motivated by recent contribution that provides answers to all these topics. An illustration of the software usage is included using real data.This research was financed by Portuguese Funds through FCT - "Fundação para a Ciência e a Tecnolo gia", within the research grant PD/BD/142887/2018. Luís Meira-Machado acknowledges financial support from the Spanish Ministry of Economy and Competitiveness MINECO through project MTM2017-82379-R funded by (AEI/FEDER, UE) and acronym "AFTERAM".R Foundation for Statistical ComputingUniversidade do MinhoSoutinho, GustavoSestelo, MartaMachado, Luís Meira20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/79140engSoutinho, G., Sestelo, M., & Meira-Machado, L. (2021). survidm: An R package for Inference and Prediction in an Illness-Death Model. The R Journal. The R Foundation. http://doi.org/10.32614/rj-2021-0702073-485910.32614/RJ-2021-070https://journal.r-project.org/archive/2021/RJ-2021-070/index.htmlinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:09:11Zoai:repositorium.sdum.uminho.pt:1822/79140Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:00:32.488595Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
survidm: An R package for Inference and Prediction in an Illness-Death Model |
title |
survidm: An R package for Inference and Prediction in an Illness-Death Model |
spellingShingle |
survidm: An R package for Inference and Prediction in an Illness-Death Model Soutinho, Gustavo multistate model illness-death multistate regression transition probabilities Ciências Naturais::Matemáticas Science & Technology |
title_short |
survidm: An R package for Inference and Prediction in an Illness-Death Model |
title_full |
survidm: An R package for Inference and Prediction in an Illness-Death Model |
title_fullStr |
survidm: An R package for Inference and Prediction in an Illness-Death Model |
title_full_unstemmed |
survidm: An R package for Inference and Prediction in an Illness-Death Model |
title_sort |
survidm: An R package for Inference and Prediction in an Illness-Death Model |
author |
Soutinho, Gustavo |
author_facet |
Soutinho, Gustavo Sestelo, Marta Machado, Luís Meira |
author_role |
author |
author2 |
Sestelo, Marta Machado, Luís Meira |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Soutinho, Gustavo Sestelo, Marta Machado, Luís Meira |
dc.subject.por.fl_str_mv |
multistate model illness-death multistate regression transition probabilities Ciências Naturais::Matemáticas Science & Technology |
topic |
multistate model illness-death multistate regression transition probabilities Ciências Naturais::Matemáticas Science & Technology |
description |
Multi-state models are a useful way of describing a process in which an individual moves through a number of finite states in continuous time. The illness-death model plays a central role in the theory and practice of these models, describing the dynamics of healthy subjects who may move to an intermediate "diseased" state before entering into a terminal absorbing state. In these models, one important goal is the modeling of transition rates which is usually done by studying the relationship between covariates and disease evolution. However, biomedical researchers are also interested in reporting other interpretable results in a simple and summarized manner. These include estimates of predictive probabilities, such as the transition probabilities, occupation probabilities, cumulative incidence functions, and the sojourn time distributions. The development of survidm package has been motivated by recent contribution that provides answers to all these topics. An illustration of the software usage is included using real data. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021 2021-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/79140 |
url |
https://hdl.handle.net/1822/79140 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Soutinho, G., Sestelo, M., & Meira-Machado, L. (2021). survidm: An R package for Inference and Prediction in an Illness-Death Model. The R Journal. The R Foundation. http://doi.org/10.32614/rj-2021-070 2073-4859 10.32614/RJ-2021-070 https://journal.r-project.org/archive/2021/RJ-2021-070/index.html |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
R Foundation for Statistical Computing |
publisher.none.fl_str_mv |
R Foundation for Statistical Computing |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799132400798662656 |