Nonparametric Estimation of Cumulative Incidence Function Based on Truncated Semi-Competing Risk Data
碩士 === 國立交通大學 === 統計學研究所 === 94 === In this thesis, we consider nonparametric estimation of the cumulative incidence function based on truncated semi-competing risk data. Peng & Fine (2006) apply the idea of decomposition to construct an estimator. Under a similar framework, we propose an altern...
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| Format: | Others |
| Language: | zh-TW |
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2006
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| Online Access: | http://ndltd.ncl.edu.tw/handle/46217903829110927101 |
| Summary: | 碩士 === 國立交通大學 === 統計學研究所 === 94 === In this thesis, we consider nonparametric estimation of the cumulative incidence function based on truncated semi-competing risk data. Peng & Fine (2006) apply the idea of decomposition to construct an estimator. Under a similar framework, we propose an alternative weighting approach. The two estimators are compared via simulations. The results show that our proposed estimator performs better which is possibly due to the fact that we make slightly stronger assumptions. We also investigate the difference between the information given by competing risks data and that given by semi-competing risks data.
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