Survival model of a parallel system with dependent failures and time varying covariates

In this paper, we extended a parallel system survival model based on the bivariate exponential to incorporate a time varying covariate. We calculated the bias, standard error and rmse of the parameter estimates of this model at different censoring levels using simulated data. We then compared the di...

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Main Authors: Arasan, Jayanthi, Lunn, Mary
Format: Article
Language:English
English
Published: Elsevier 2008
Online Access:http://psasir.upm.edu.my/id/eprint/7021/
http://psasir.upm.edu.my/id/eprint/7021/1/Survival%20model%20of%20a%20parallel%20system%20with%20dependent%20failures%20and%20time%20varying%20covariates.pdf
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author Arasan, Jayanthi
Lunn, Mary
author_facet Arasan, Jayanthi
Lunn, Mary
author_sort Arasan, Jayanthi
building UPM Institutional Repository
collection Online Access
description In this paper, we extended a parallel system survival model based on the bivariate exponential to incorporate a time varying covariate. We calculated the bias, standard error and rmse of the parameter estimates of this model at different censoring levels using simulated data. We then compared the difference in the total error when a fixed covariate model was used instead of the true time varying covariate model. Following that, we studied three methods of constructing confidence intervals for such models and conclusions were drawn based on the results of the coverage probability study. Finally, the results obtained by fitting the diabetic retinopathy study data to the model were analysed.
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spelling upm-70212015-12-04T09:02:40Z http://psasir.upm.edu.my/id/eprint/7021/ Survival model of a parallel system with dependent failures and time varying covariates Arasan, Jayanthi Lunn, Mary In this paper, we extended a parallel system survival model based on the bivariate exponential to incorporate a time varying covariate. We calculated the bias, standard error and rmse of the parameter estimates of this model at different censoring levels using simulated data. We then compared the difference in the total error when a fixed covariate model was used instead of the true time varying covariate model. Following that, we studied three methods of constructing confidence intervals for such models and conclusions were drawn based on the results of the coverage probability study. Finally, the results obtained by fitting the diabetic retinopathy study data to the model were analysed. Elsevier 2008 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/7021/1/Survival%20model%20of%20a%20parallel%20system%20with%20dependent%20failures%20and%20time%20varying%20covariates.pdf Arasan, Jayanthi and Lunn, Mary (2008) Survival model of a parallel system with dependent failures and time varying covariates. Journal of Statistical Planning and Inference, 139 (3). pp. 944-951. ISSN 0378-3758 http://dx.doi.org/10.1016/j.jspi.2008.06.007 10.1016/j.jspi.2008.06.007 English
spellingShingle Arasan, Jayanthi
Lunn, Mary
Survival model of a parallel system with dependent failures and time varying covariates
title Survival model of a parallel system with dependent failures and time varying covariates
title_full Survival model of a parallel system with dependent failures and time varying covariates
title_fullStr Survival model of a parallel system with dependent failures and time varying covariates
title_full_unstemmed Survival model of a parallel system with dependent failures and time varying covariates
title_short Survival model of a parallel system with dependent failures and time varying covariates
title_sort survival model of a parallel system with dependent failures and time varying covariates
url http://psasir.upm.edu.my/id/eprint/7021/
http://psasir.upm.edu.my/id/eprint/7021/
http://psasir.upm.edu.my/id/eprint/7021/
http://psasir.upm.edu.my/id/eprint/7021/1/Survival%20model%20of%20a%20parallel%20system%20with%20dependent%20failures%20and%20time%20varying%20covariates.pdf