A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction
Many medical investigations generate both repeatedly-measured (longitudinal)biomarker and survival data. One of complex issue arises when investigating the association between longitudinal and time-to-event data when there are cured patients in the population, which leads to a plateau in the surviva...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
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EuroJournals Publishing Inc.
2007
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| Online Access: | http://psasir.upm.edu.my/id/eprint/7671/ http://psasir.upm.edu.my/id/eprint/7671/1/A%20Semiparametric%20Joint%20Model%20for%20Longitudinal%20and%20Time.pdf |
| _version_ | 1848840661104590848 |
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| author | Abu Bakar, Mohd Rizam A. Salah, Khalid Ibrahim, Noor Akma Haron, Kassim |
| author_facet | Abu Bakar, Mohd Rizam A. Salah, Khalid Ibrahim, Noor Akma Haron, Kassim |
| author_sort | Abu Bakar, Mohd Rizam |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Many medical investigations generate both repeatedly-measured (longitudinal)biomarker and survival data. One of complex issue arises when investigating the association between longitudinal and time-to-event data when there are cured patients in the population, which leads to a plateau in the survival function S(t) after sufficient follow-up. Thus, usual Cox proportional hazard model Cox (1972) is not applicable since the proportional hazard assumption is violated. An alternative is to consider survival models incorporating a cure fraction. In this paper we present a new class of joint model for univariate longitudinal and survival data in presence of cure fraction. For the longitudinal model, a stochastic Integrated Ornstein-Uhlenbeck process will present, and for the survival model a semiparametric survival function will be considered which accommodate both zero and non-zero cure fractions of the dynamic disease progression. Moreover, we consider a Bayesian approach which is motivated by the complexity of the model. Posterior and prior specification needs to accommodate parameter constraints due to the nonnegativity of the survival function. A simulation study is presented to evaluate the performance of this joint model. |
| first_indexed | 2025-11-15T07:30:53Z |
| format | Article |
| id | upm-7671 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T07:30:53Z |
| publishDate | 2007 |
| publisher | EuroJournals Publishing Inc. |
| recordtype | eprints |
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| spelling | upm-76712015-12-08T09:02:38Z http://psasir.upm.edu.my/id/eprint/7671/ A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction Abu Bakar, Mohd Rizam A. Salah, Khalid Ibrahim, Noor Akma Haron, Kassim Many medical investigations generate both repeatedly-measured (longitudinal)biomarker and survival data. One of complex issue arises when investigating the association between longitudinal and time-to-event data when there are cured patients in the population, which leads to a plateau in the survival function S(t) after sufficient follow-up. Thus, usual Cox proportional hazard model Cox (1972) is not applicable since the proportional hazard assumption is violated. An alternative is to consider survival models incorporating a cure fraction. In this paper we present a new class of joint model for univariate longitudinal and survival data in presence of cure fraction. For the longitudinal model, a stochastic Integrated Ornstein-Uhlenbeck process will present, and for the survival model a semiparametric survival function will be considered which accommodate both zero and non-zero cure fractions of the dynamic disease progression. Moreover, we consider a Bayesian approach which is motivated by the complexity of the model. Posterior and prior specification needs to accommodate parameter constraints due to the nonnegativity of the survival function. A simulation study is presented to evaluate the performance of this joint model. EuroJournals Publishing Inc. 2007 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/7671/1/A%20Semiparametric%20Joint%20Model%20for%20Longitudinal%20and%20Time.pdf Abu Bakar, Mohd Rizam and A. Salah, Khalid and Ibrahim, Noor Akma and Haron, Kassim (2007) A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction. European Journal of Scientific Research, 18 (4). pp. 707-729. ISSN 1450-216X http://www.eurojournals.com/ejsr.htm English |
| spellingShingle | Abu Bakar, Mohd Rizam A. Salah, Khalid Ibrahim, Noor Akma Haron, Kassim A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction |
| title | A Semiparametric Joint Model for Longitudinal and Time-to-
Event Univariate Data in Presence of Cure Fraction |
| title_full | A Semiparametric Joint Model for Longitudinal and Time-to-
Event Univariate Data in Presence of Cure Fraction |
| title_fullStr | A Semiparametric Joint Model for Longitudinal and Time-to-
Event Univariate Data in Presence of Cure Fraction |
| title_full_unstemmed | A Semiparametric Joint Model for Longitudinal and Time-to-
Event Univariate Data in Presence of Cure Fraction |
| title_short | A Semiparametric Joint Model for Longitudinal and Time-to-
Event Univariate Data in Presence of Cure Fraction |
| title_sort | semiparametric joint model for longitudinal and time-to-
event univariate data in presence of cure fraction |
| url | http://psasir.upm.edu.my/id/eprint/7671/ http://psasir.upm.edu.my/id/eprint/7671/ http://psasir.upm.edu.my/id/eprint/7671/1/A%20Semiparametric%20Joint%20Model%20for%20Longitudinal%20and%20Time.pdf |