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Koomesh

Journal of Semnan University of Medical Sciences

e-ISSN 2345-3699
p-ISSN 1608-7046
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Cover image of the article: Time-dependent frailty model to gap times between recurrent events with application to epilepsy data

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Outline

Time-dependent frailty model to gap times between recurrent events with application to epilepsy data

Authors

Samaneh HossainzadehSamaneh Hossainzadeh ORCID,*, Soghrat Faghihzadeh, Mehdi Rahgozar, Ebrahim Hajizadeh, Seyed Sohrab Hashemi Fesharaki, Marzieh Gharakhani
*Corresponding Author: Email: sa.hosseinzadeh@uswr.ac.ir
Koomesh:Vol. 17, issue 3; 761-771
Published online:Sep 28, 2016
Article type:Research Article
Received:Jun 01, 2015
Accepted:Oct 02, 2015
How to Cite:Hossainzadeh S, Faghihzadeh S, Rahgozar M, Hajizadeh E, Hashemi Fesharaki SS, et al. Time-dependent frailty model to gap times between recurrent events with application to epilepsy data. koomesh. 2016;17(3):e151227. doi:

Abstract

Introduction: In recurrent event a specific event occur repeatedly over time for a person. The frailty models take into account this correlation and provide efficient inferences. The frailties are assumed to be constant over time that it may be insufficient. Therefore time-varying frailty models are more realistic models. The aim of this study was to fit a time-dependent frailty model in the gap time between recurrent events. Materials and methods: In this study, a time-dependent frailty model was introduced in the gap time between recurrent events, that was a generalization of the Wintrebert (2004) model in cluster data (center-effect). The parameters were estimated by Gaussian quadrature method. The model was applied to epilepsy data. Results: The time-dependent frailty model fitted better in compare to shared frailty model. The observation time for IED on EEG in 56 patients (%73 male, %34 veteran status) with epilepsy was studied. Age and veteran status were the two risk factors in the gap time between IEDs. Variance of frailty was significant too. Conclusion: The result of time-dependent frailty model was reliable when there were unknown time-dependent factors in medical data and make changes on times of occurring recurrent events. The Gaussian quadrature was an applied method to fit a time-dependent frailty model. The programming for this method was comfortable hence this method can cause time-dependent fraility models to be more practical in medical studies.

Highlights

KeywordsTime-Dependent FrailtyRecurrent EventGaussian QuadratureEpilepsyشکنندگی وابسته به زمانحوادث بازگشتیمربع‌بندی گاوسیصرع.

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Copyright

© 2016, Author(s). This open-access article is available under the Creative Commons Attribution 4.0 (CC BY 4.0) International License (https://creativecommons.org/licenses/by/4.0/), which allows for unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.

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