A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure Times

<p>We present a Bayesian approach for analysis of competing risks survival data with masked causes of failure. This approach is often used to assess the impact of covariates on the hazard functions when the failure time is exactly observed for some subjects but only known to lie in an interval...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي: Yosra Yousif (14570989) (author)
مؤلفون آخرون: Faiz A. M. Elfaki (14570992) (author), Meftah Hrairi (14570995) (author), Oyelola A. Adegboye (4287826) (author)
منشور في: 2023
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author Yosra Yousif (14570989)
author2 Faiz A. M. Elfaki (14570992)
Meftah Hrairi (14570995)
Oyelola A. Adegboye (4287826)
author2_role author
author
author
author_facet Yosra Yousif (14570989)
Faiz A. M. Elfaki (14570992)
Meftah Hrairi (14570995)
Oyelola A. Adegboye (4287826)
author_role author
dc.creator.none.fl_str_mv Yosra Yousif (14570989)
Faiz A. M. Elfaki (14570992)
Meftah Hrairi (14570995)
Oyelola A. Adegboye (4287826)
dc.date.none.fl_str_mv 2023-03-15T11:50:47Z
dc.identifier.none.fl_str_mv 10.1155/2020/8248640
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/A_Bayesian_Approach_to_Competing_Risks_Model_with_Masked_Causes_of_Failure_and_Incomplete_Failure_Times/22014902
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Mathematical sciences
Statistics
Bayesian approach
Competing risks
Survival data
Masked causes of failure
Partly interval-censored data
Covariates
dc.title.none.fl_str_mv A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure Times
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p>We present a Bayesian approach for analysis of competing risks survival data with masked causes of failure. This approach is often used to assess the impact of covariates on the hazard functions when the failure time is exactly observed for some subjects but only known to lie in an interval of time for the remaining subjects. Such data, known as partly interval-censored data, usually result from periodic inspection in production engineering. In this study, Dirichlet and Gamma processes are assumed as priors for masking probabilities and baseline hazards. Markov chain Monte Carlo (MCMC) technique is employed for the implementation of the Bayesian approach. The effectiveness of the proposed approach is illustrated with simulated and production engineering applications. </p> <h2>Other information </h2> <p>Published in: Mathematical Problems in Engineering<br> License: <a href="http://creativecommons.org/licenses/by/4.0" target="_blank">http://creativecommons.org/licenses/by/4.0</a><br> See article on publisher's website: <a href="http://dx.doi.org/10.1155/2020/8248640" target="_blank">http://dx.doi.org/10.1155/2020/8248640</a> </p>
eu_rights_str_mv openAccess
id Manara2_681673dfdd07b20c7385df689ab7f065
identifier_str_mv 10.1155/2020/8248640
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/22014902
publishDate 2023
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rights_invalid_str_mv CC BY 4.0
spelling A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure TimesYosra Yousif (14570989)Faiz A. M. Elfaki (14570992)Meftah Hrairi (14570995)Oyelola A. Adegboye (4287826)Mathematical sciencesStatisticsBayesian approachCompeting risksSurvival dataMasked causes of failurePartly interval-censored dataCovariates<p>We present a Bayesian approach for analysis of competing risks survival data with masked causes of failure. This approach is often used to assess the impact of covariates on the hazard functions when the failure time is exactly observed for some subjects but only known to lie in an interval of time for the remaining subjects. Such data, known as partly interval-censored data, usually result from periodic inspection in production engineering. In this study, Dirichlet and Gamma processes are assumed as priors for masking probabilities and baseline hazards. Markov chain Monte Carlo (MCMC) technique is employed for the implementation of the Bayesian approach. The effectiveness of the proposed approach is illustrated with simulated and production engineering applications. </p> <h2>Other information </h2> <p>Published in: Mathematical Problems in Engineering<br> License: <a href="http://creativecommons.org/licenses/by/4.0" target="_blank">http://creativecommons.org/licenses/by/4.0</a><br> See article on publisher's website: <a href="http://dx.doi.org/10.1155/2020/8248640" target="_blank">http://dx.doi.org/10.1155/2020/8248640</a> </p>2023-03-15T11:50:47ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1155/2020/8248640https://figshare.com/articles/journal_contribution/A_Bayesian_Approach_to_Competing_Risks_Model_with_Masked_Causes_of_Failure_and_Incomplete_Failure_Times/22014902CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/220149022023-03-15T11:50:47Z
spellingShingle A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure Times
Yosra Yousif (14570989)
Mathematical sciences
Statistics
Bayesian approach
Competing risks
Survival data
Masked causes of failure
Partly interval-censored data
Covariates
status_str publishedVersion
title A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure Times
title_full A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure Times
title_fullStr A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure Times
title_full_unstemmed A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure Times
title_short A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure Times
title_sort A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure Times
topic Mathematical sciences
Statistics
Bayesian approach
Competing risks
Survival data
Masked causes of failure
Partly interval-censored data
Covariates