Estimators of quantile difference between two samples with length-biased and right-censored data

被引:3
|
作者
Xun, Li [1 ]
Tao, Li [1 ]
Zhou, Yong [2 ]
机构
[1] Changchun Univ Technol, Sch Math & Stat, Changchun 130012, Jilin, Peoples R China
[2] East China Normal Univ, Acad Stat & Interdisciplinary Sci, MOE, Key Lab Adv Theory & Applicat Stat & Data Sci, Shanghai 200062, Peoples R China
基金
中国国家自然科学基金;
关键词
Quantile difference; Length bias; Estimating equation; Kernel function; Inverse probability weight; PREVALENT COHORT; INFERENCE; SURVIVAL; OSCAR;
D O I
10.1007/s11749-019-00657-3
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper, the difference between the quantiles of two samples is investigated. One sample comes from a prevalent cohort with a stable incidence rate. Then, the observed survival times are length-biased and right-censored data. Another sample is drawn from an incident cohort study with right-censored data. We estimate the quantile difference based on different estimating equations. That is because the estimating equation estimators have higher efficiency than the difference of two one-sample quantile estimators in the sense of minimizing the mean squared error. Moreover, the consistency and asymptotic normality of these estimators are established. Then, the confidence intervals of quantile difference can be constructed by using the normal approximations. Finally, the performance of the proposed methods is presented in the numerical studies, especially with small sample sizes.
引用
收藏
页码:409 / 429
页数:21
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