Quantile function regression analysis for interval censored data, with application to salary survey data
學年 109
學期 2
出版（發表）日期 2021-03-22
作品名稱 Quantile function regression analysis for interval censored data, with application to salary survey data
作品名稱（其他語言）
著者 Hsu CY; Wen CC; Chen YH
單位
出版者
著錄名稱、卷期、頁數 Japanese Journal of Statistics and Data Science 4, p.999-1018
摘要 This study aims at regression analysis for quantile functions where the quantile regression coefficients are treated as functions over a continuum of quantile levels. We propose a general inference procedure for quantile regression coefficient functions with interval-censored outcome data. The modeling framework follows a recent proposal using a set of parametric basis functions to approximate the quantile regression coefficient functions. The new proposal can accommodate outcome data subject to general types of interval censoring, including fixed, random, and partly interval censoring. The large sample theory for the proposed estimator is established for inference, and a goodness-of-fit testing procedure is developed to guide the choice of the basis functions. We apply the proposed methodology to a survey dataset on monthly salaries of Taiwan workers, where only parts of the salary data are exact while the others are interval-censored according to the salary intervals prespecified in the survey questionnaire.
關鍵字 Goodness-of-fit test;Interval censoring;Parametric model;Quantile regression;Truncation
語言 en_US
ISSN 2520-8764
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/122344 )