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 en_US
ISSN 1380-7870;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 是
國別 USA
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/105922 )