Methods for checking the markov condition in multi-state survival data
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2019 |
| Outros Autores: | , |
| Idioma: | eng |
| Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Texto Completo: | http://hdl.handle.net/1822/69576 |
Resumo: | The inference in multi-state models is traditionally performed under a Markov assumption. This assumption claims that given the present state, the future evolution of the process is independent of the states previously visited and the transition times among them. Usually, this assumption is checked including covariates depending on the history. However, since the landmark methods of the transition probabilities proposed by de Uña-Alvarez and Meira-Machado (2015), and by Putter and Spitoni (2018) are free of the Markov assumption, they can also be used to introduce such tests (at least in the scope of the progressive multi-state models) by measuring their discrepancy to Markovian estimators. In this paper, we introduce two local tests for the Markov assumption and compare them with the usual approach based on local future-past association through simulations. An application to a clinical trial on colon cancer is included. |
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Methods for checking the markov condition in multi-state survival dataCensoringMarkov assumptionMulti-state modelsTransition probabilitiesCiências Naturais::MatemáticasThe inference in multi-state models is traditionally performed under a Markov assumption. This assumption claims that given the present state, the future evolution of the process is independent of the states previously visited and the transition times among them. Usually, this assumption is checked including covariates depending on the history. However, since the landmark methods of the transition probabilities proposed by de Uña-Alvarez and Meira-Machado (2015), and by Putter and Spitoni (2018) are free of the Markov assumption, they can also be used to introduce such tests (at least in the scope of the progressive multi-state models) by measuring their discrepancy to Markovian estimators. In this paper, we introduce two local tests for the Markov assumption and compare them with the usual approach based on local future-past association through simulations. An application to a clinical trial on colon cancer is included.This research was financed by Portuguese Funds through FCT - “Fundaçãao para a Ciência e a Tecnologia”, within the research grants PTDC/MAT-STA/28248/2017 and PD/BD/142887/2018Universidade do MinhoSoutinho, Gustavo Domingos Costa CoelhoMachado, Luís MeiraOliveira, Pedro Nuno Ferreira Pinto20192019-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/69576enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T06:28:38Zoai:repositorium.sdum.uminho.pt:1822/69576Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:54:20.852172Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Methods for checking the markov condition in multi-state survival data |
| title |
Methods for checking the markov condition in multi-state survival data |
| spellingShingle |
Methods for checking the markov condition in multi-state survival data Soutinho, Gustavo Domingos Costa Coelho Censoring Markov assumption Multi-state models Transition probabilities Ciências Naturais::Matemáticas |
| title_short |
Methods for checking the markov condition in multi-state survival data |
| title_full |
Methods for checking the markov condition in multi-state survival data |
| title_fullStr |
Methods for checking the markov condition in multi-state survival data |
| title_full_unstemmed |
Methods for checking the markov condition in multi-state survival data |
| title_sort |
Methods for checking the markov condition in multi-state survival data |
| author |
Soutinho, Gustavo Domingos Costa Coelho |
| author_facet |
Soutinho, Gustavo Domingos Costa Coelho Machado, Luís Meira Oliveira, Pedro Nuno Ferreira Pinto |
| author_role |
author |
| author2 |
Machado, Luís Meira Oliveira, Pedro Nuno Ferreira Pinto |
| author2_role |
author author |
| dc.contributor.none.fl_str_mv |
Universidade do Minho |
| dc.contributor.author.fl_str_mv |
Soutinho, Gustavo Domingos Costa Coelho Machado, Luís Meira Oliveira, Pedro Nuno Ferreira Pinto |
| dc.subject.por.fl_str_mv |
Censoring Markov assumption Multi-state models Transition probabilities Ciências Naturais::Matemáticas |
| topic |
Censoring Markov assumption Multi-state models Transition probabilities Ciências Naturais::Matemáticas |
| description |
The inference in multi-state models is traditionally performed under a Markov assumption. This assumption claims that given the present state, the future evolution of the process is independent of the states previously visited and the transition times among them. Usually, this assumption is checked including covariates depending on the history. However, since the landmark methods of the transition probabilities proposed by de Uña-Alvarez and Meira-Machado (2015), and by Putter and Spitoni (2018) are free of the Markov assumption, they can also be used to introduce such tests (at least in the scope of the progressive multi-state models) by measuring their discrepancy to Markovian estimators. In this paper, we introduce two local tests for the Markov assumption and compare them with the usual approach based on local future-past association through simulations. An application to a clinical trial on colon cancer is included. |
| publishDate |
2019 |
| dc.date.none.fl_str_mv |
2019 2019-01-01T00:00:00Z |
| dc.type.driver.fl_str_mv |
conference paper |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/69576 |
| url |
http://hdl.handle.net/1822/69576 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| 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.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
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FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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RCAAP |
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RCAAP |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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