教師資料查詢 | 類別: 期刊論文 | 教師: 溫啟仲 WEN,CHI-CHUNG (瀏覽個人網頁)

標題:A functional inference for multivariate current status data with mismeasured covariate
學年103
學期2
出版(發表)日期2015/07/01
作品名稱A functional inference for multivariate current status data with mismeasured covariate
作品名稱(其他語言)
著者Wen, Chi-Chung; Huang, Yih-Huei; Wu, Yuh-Jenn
單位
出版者
著錄名稱、卷期、頁數Lifetime Data Analysis 21(3), p.379-396
摘要Covariate measurement error problems have been recently studied for current status failure time data but not yet for multivariate current status data. Motivated by the three-hypers dataset from a health survey study, where the failure times for three-hypers (hyperglycemia, hypertension, hyperlipidemia) are subject to current status censoring and the covariate self-reported body mass index may be subject to measurement error, we propose a functional inference method under the proportional odds model for multivariate current status data with mismeasured covariates. The new proposal utilizes the working independence strategy to handle correlated current status observations from the same subject, as well as the conditional score approach to handle mismeasured covariate without specifying the covariate distribution. The asymptotic theory, together with a stable computation procedure combining the Newton–Raphson and self-consistency algorithms, is established for the proposed estimation method. We evaluate the method through simulation studies and illustrate it with three-hypers data.
關鍵字Conditional score;Correlated data;Measurement error;Proportional odds model;Self-consistency
語言英文(美國)
ISSN1380-7870;1572-9249
期刊性質國外
收錄於SCI;
產學合作
通訊作者Wen, Chi-Chung
審稿制度
國別美國
公開徵稿
出版型式,電子版
相關連結
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