Estimation of rank correlation coefficient for two serial gap times in the presence of induced informative censoring

碩士 === 國立臺灣大學 === 流行病學研究所 === 97 === In follow-up studies, bivariate event data are often encountered when subjects may experience two events with different or the same types. In analyzing bivariate event data, two types of time scale are considered in the literature: the times to events and the tim...

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Main Authors: Tsung-Chiang Fu, 傅宗襁
Other Authors: Shu-hui Chang
Format: Others
Language:zh-TW
Published: 2009
Online Access:http://ndltd.ncl.edu.tw/handle/86094025504589048844
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spelling ndltd-TW-097NTU055440122016-05-04T04:31:49Z http://ndltd.ncl.edu.tw/handle/86094025504589048844 Estimation of rank correlation coefficient for two serial gap times in the presence of induced informative censoring 具誘導訊息設限之二元有序間隔時間的排序相關係數估計 Tsung-Chiang Fu 傅宗襁 碩士 國立臺灣大學 流行病學研究所 97 In follow-up studies, bivariate event data are often encountered when subjects may experience two events with different or the same types. In analyzing bivariate event data, two types of time scale are considered in the literature: the times to events and the times between adjacent events. When the occurrence of during follow-up two events is in a chronological order, the gap time, defined as the time between adjacent events, is often of interest in the study. In the literature, measures of association between bivariate event times have been studied, but not yet for two serial gap times. In general, standard techniques for analyzing the times to events are inappropriate for analyzing the second gap time due to the presence of induced informative censoring. In this paper, Kendall''s tau is considered as a measure of association between gap times. Nonparametric estimation of Kendall’s tau for two serial gap times is proposed in which inverse probability of censoring weights is used to accommodate the bias from induced informative censoring. Asymptotic normality of the proposed estimator of Kendall''s tau is obtained by employing the theory of U statistics along with martingale techniques. Finally, the performance of the proposed method is illustrated by a simulation study. Shu-hui Chang 張淑惠 2009 學位論文 ; thesis 59 zh-TW
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description 碩士 === 國立臺灣大學 === 流行病學研究所 === 97 === In follow-up studies, bivariate event data are often encountered when subjects may experience two events with different or the same types. In analyzing bivariate event data, two types of time scale are considered in the literature: the times to events and the times between adjacent events. When the occurrence of during follow-up two events is in a chronological order, the gap time, defined as the time between adjacent events, is often of interest in the study. In the literature, measures of association between bivariate event times have been studied, but not yet for two serial gap times. In general, standard techniques for analyzing the times to events are inappropriate for analyzing the second gap time due to the presence of induced informative censoring. In this paper, Kendall''s tau is considered as a measure of association between gap times. Nonparametric estimation of Kendall’s tau for two serial gap times is proposed in which inverse probability of censoring weights is used to accommodate the bias from induced informative censoring. Asymptotic normality of the proposed estimator of Kendall''s tau is obtained by employing the theory of U statistics along with martingale techniques. Finally, the performance of the proposed method is illustrated by a simulation study.
author2 Shu-hui Chang
author_facet Shu-hui Chang
Tsung-Chiang Fu
傅宗襁
author Tsung-Chiang Fu
傅宗襁
spellingShingle Tsung-Chiang Fu
傅宗襁
Estimation of rank correlation coefficient for two serial gap times in the presence of induced informative censoring
author_sort Tsung-Chiang Fu
title Estimation of rank correlation coefficient for two serial gap times in the presence of induced informative censoring
title_short Estimation of rank correlation coefficient for two serial gap times in the presence of induced informative censoring
title_full Estimation of rank correlation coefficient for two serial gap times in the presence of induced informative censoring
title_fullStr Estimation of rank correlation coefficient for two serial gap times in the presence of induced informative censoring
title_full_unstemmed Estimation of rank correlation coefficient for two serial gap times in the presence of induced informative censoring
title_sort estimation of rank correlation coefficient for two serial gap times in the presence of induced informative censoring
publishDate 2009
url http://ndltd.ncl.edu.tw/handle/86094025504589048844
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