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KCI 등재 SCOPUS
Analysis of Recurrent Gap Time Data with a Binary Time-Varying Covariate
( Yang Jin Kim )
UCI I410-ECN-0102-2015-300-002284826
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Recurrent gap times are analyzed with diverse methods under several assumptions such as a marginal model or a frailty model. Several resampling techniques have been recently suggested to estimate the covariate effect; however, these approaches can be applied with a time-fixed covariate. According to simulation results, these methods result in biased estimates for a time-varying covariate which is often observed in a longitudinal study. In this paper, we extend a resampling method by incorporating new weights and sampling scheme. Simulation studies are performed to compare the suggested method with previous resampling methods. The proposed method is applied to estimate the e.ect of an educational program on traffic conviction data where a program participation occurs in the middle of the study.

1. Introduction
2. Covariate Weighted Analysis
3. Simulation
4. Data Analysis
5. Concluding Remarks
References
[자료제공 : 네이버학술정보]
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