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:: Volume 8, Issue 1 (9-2014) ::
JSS 2014, 8(1): 57-74 Back to browse issues page
A Semiparametric Model for Recurrent Event Data with Excess Zero under Competing Risks
Ali Sharifi , SeyedReza Hashemi *
Abstract:   (17591 Views)
A semiparametric additive-multiplicative intensity function for recurrent events data under two competing risks have been supposed in this paper. The model contains unknown baseline hazard function that defined separately intensity function for different competing risks effects on subjects failure. The presented model is based on regression parameters for effective covariates and frailty variable which describe correlation between terminal event and recurrent events and personal difference of under study subjects. The model support right censored and informative censored survival data. For estimating unknown parameters, numerical methods have been used and baseline hazard parameters are approximated using Taylor series expansion. A simulation study and application of the model to the bone marrow transplantation data are performed to illustrate the performance of the proposed model.
Keywords: Semiparametric Model, Intensity Function, Baseline Hazard Function, Recurrent Event Data, Competing Risks, Frailty Variable
Full-Text [PDF 475 kb]   (3007 Downloads)    
Type of Study: Applied | Subject: Biostatistics
Received: 2013/09/25 | Accepted: 2014/05/9 | Published: 2014/05/9
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Sharifi A, Hashemi S. A Semiparametric Model for Recurrent Event Data with Excess Zero under Competing Risks. JSS 2014; 8 (1) :57-74
URL: http://jss.irstat.ir/article-1-235-en.html


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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 8, Issue 1 (9-2014) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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