【摘要】 本文旨在建立一个存在不可忽略的无响应缺失时高维协变量向量的协变量选择方法.由于有不可忽略的缺失响应数据,必须建立一种新的协变量选择方法来删除既与响应变量也与缺失机制无关的协变量.一旦冗余协变量被删除,现有的缺失机制估计和其他基于逆缺失机制加权的分析方法可以被应用.我们提供了一些模拟结果来展示我们方法的有效性.更多还原

【Abstract】 This paper aims at developing a covariate selection approach for high-dimensional covariate vector in the presence of nonignorable nonresponse. Because of nonignorable missing responses, a novel covariate selection method has to be developed to eliminate covariates associated with neither the response variable nor the nonresponse mechanism. Once the redundant covariates are removed, existing methods for propensity estimation and other analyses by inverse propensity weighting can be applied. We provide some simulation results to show the effectiveness of our approach.更多还原