Published auxiliary information can be helpful in conducting statistical inference in a new study. In this paper, we synthesize the auxiliary information with semiparametric likelihood-based inference for censoring data with the total sample size is available. We express the auxiliary information as constraints on the regression coefficients and the covariate distribution, then use empirical likelihood method for general estimating equations to improve the efficiency of the interested parameters in the specified model. The consistency and asymptotic normality of the resulting regression parameter estimators established. Also numerical simulation and application with different supposed conditions show that the proposed method yields a substantial gain in efficiency of the interested parameters.

中文翻译：

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基于来自外部海量数据源的辅助信息的截尾数据的半参数似然推理

已发布的辅助信息有助于在新研究中进行统计推断。在本文中，我们将辅助信息与基于半参数似然的推理合成，用于审查总样本量可用的数据。我们将辅助信息表示为对回归系数和协变量分布的约束，然后使用经验似然法进行一般估计方程，以提高指定模型中感兴趣参数的效率。建立了所得回归参数估计量的一致性和渐近正态性。不同假设条件下的数值模拟和应用表明，所提出的方法在感兴趣参数的效率方面产生了实质性的提高。