The estimation method for clustered failure time data

碩士 === 國立臺北大學 === 統計學系 === 106 === Joint likelihood estimation and pairwise likelihood estimation for clustered data in multivariate failure time (MVFT) are evaluated, and data are assumed to have a characteristic of competing risks. This study will consider two or three observations per cluster and...

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Main Authors: YANG,MIN-JU, 楊閔茹
Other Authors: HUANG, CHIA-HUI
Format: Others
Language:zh-TW
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/nez45q
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spelling ndltd-TW-106NTPU03370092019-05-16T00:37:29Z http://ndltd.ncl.edu.tw/handle/nez45q The estimation method for clustered failure time data 群聚型存活資料的估計方法 YANG,MIN-JU 楊閔茹 碩士 國立臺北大學 統計學系 106 Joint likelihood estimation and pairwise likelihood estimation for clustered data in multivariate failure time (MVFT) are evaluated, and data are assumed to have a characteristic of competing risks. This study will consider two or three observations per cluster and use Weibull distribution as the marginal distribution and different Copula to construct a joint survival distribution. Using statistical software to simulate data, parameter estimation is performed. The main estimated parameters are the parameters in the marginal distribution and the dependence parameter in the Copula. The simulation results of the joint likelihood estimation are well, and they have good performance on the evaluation index; the pairwise likelihood estimation is not stable enough, and only meets the evaluation criteria in some cases. HUANG, CHIA-HUI 黃佳慧 2018 學位論文 ; thesis 34 zh-TW
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language zh-TW
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description 碩士 === 國立臺北大學 === 統計學系 === 106 === Joint likelihood estimation and pairwise likelihood estimation for clustered data in multivariate failure time (MVFT) are evaluated, and data are assumed to have a characteristic of competing risks. This study will consider two or three observations per cluster and use Weibull distribution as the marginal distribution and different Copula to construct a joint survival distribution. Using statistical software to simulate data, parameter estimation is performed. The main estimated parameters are the parameters in the marginal distribution and the dependence parameter in the Copula. The simulation results of the joint likelihood estimation are well, and they have good performance on the evaluation index; the pairwise likelihood estimation is not stable enough, and only meets the evaluation criteria in some cases.
author2 HUANG, CHIA-HUI
author_facet HUANG, CHIA-HUI
YANG,MIN-JU
楊閔茹
author YANG,MIN-JU
楊閔茹
spellingShingle YANG,MIN-JU
楊閔茹
The estimation method for clustered failure time data
author_sort YANG,MIN-JU
title The estimation method for clustered failure time data
title_short The estimation method for clustered failure time data
title_full The estimation method for clustered failure time data
title_fullStr The estimation method for clustered failure time data
title_full_unstemmed The estimation method for clustered failure time data
title_sort estimation method for clustered failure time data
publishDate 2018
url http://ndltd.ncl.edu.tw/handle/nez45q
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