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.

中文翻译：

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具有长度偏向和右删失数据的两个样本之间的分位数差异的估计量

本文研究了两个样本分位数之间的差异。一个样本来自具有稳定发病率的流行人群。然后，将观察到的生存时间作为长度偏向和右删失的数据。另一个样本是从具有正确删节数据的事件队列研究中得出的。我们根据不同的估算方程估算分位数差异。这是因为在最小化均方误差的意义上，估计方程估计器具有比两个一样本分位数估计器之差更高的效率。此外，建立了这些估计量的一致性和渐近正态性。然后，可以使用正态近似构造分位数差的置信区间。最后，数值研究显示了所提出方法的性能，