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

Li Xun (), Li Tao and Yong Zhou
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Li Xun: Changchun University of Technology
Li Tao: Changchun University of Technology
Yong Zhou: East China Normal University

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2020, vol. 29, issue 2, No 8, 409-429

Abstract: Abstract 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.

Keywords: Quantile difference; Length bias; Estimating equation; Kernel function; Inverse probability weight; 62N86 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11749-019-00657-3

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