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Activity Number:
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470
- Lifetime Risk, Competing Risk, and Recurrent Events
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Type:
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Contributed
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Date/Time:
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Thursday, August 6, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Lifetime Data Science Section
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Abstract #312180
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Title:
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Joint Rate Regression Models for Bivariate Recurrent Events with Frailty Processes
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Author(s):
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Yuxin Zhu* and Mei-Cheng Wang
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Companies:
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and Johns Hopkins University
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Keywords:
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bivariate recurrent event;
frailty process;
correlation;
composite likelihood;
estimating equation ;
GMM
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Abstract:
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Bivariate or multivariate recurrent event data are often collected in longitudinal studies as the primary outcome measurements for research. We consider statistical modeling for bivariate recurrent events, where the association between two types of recurrent events is characterised by frailty processes and hence allows for time- dependent association. This forms a contrast with conventional models for bivariate recurrent evnts where the association is characterised solely by a baseline frailty variable. A bivariate partial likelihood approach is developed to estimate parameters in the joint rate models in semiparametric settings. The proposed model and method can be used to identify biomarkers or risk factors for recurrent events correlations that could be used to tailor preventive strategies and treatment plans.
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Authors who are presenting talks have a * after their name.
