Abstract An adjusted least absolute deviation estimating function, founded on the inverse (probability of) censoring weighted approach, is proposed. Covariate-free left and right censoring is assumed. When left censoring is absent, the proposed estimating function reduces to its right-censored counterpart. Consistency and asymptotic normality of the estimator of the regression parameter are derived. Finite sample performance is investigated via simulations. Application of the proposed method is illustrated using some synthetic data sets.

中文翻译：

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两次删失数据的中值回归

摘要 提出了一种基于删失加权逆（概率）方法的调整最小绝对偏差估计函数。假设无协变量左右删失。当不存在左删失时，建议的估计函数减少到其右删失对应物。推导出回归参数估计量的一致性和渐近正态性。通过模拟研究有限样本性能。使用一些合成数据集说明了所提出方法的应用。