在零膨胀数据插补的情况下保持调查中的分布函数
Preserving the distribution function in surveys in case of imputation for zero inflated data
摘要：
调查中的项目无回答通常采用单次插补方法处理，其主要目的是减少无回答偏倚。插补方法需要适应研究变量。例如，在商业调查中，兴趣变量通常包含大量的零。受混合回归模型的启发，我们提出了两种插补方法，并研究了它们的统计特性。我们表明，这些程序保持分布函数，如果插补模型是指定的。仿真研究的结果表明，所提出的方法在偏差和均方误差方面具有良好的性能。
英文摘要：
Item non-response in surveys is usually handled by single imputation, whose main objective is to reduce the non-response bias. Imputation methods need to be adapted to the study variable. For instance, in business surveys, the interest variables often contain a large number of zeros. Motivated by a mixture regression model, we propose two imputation procedures for such data and study their statistical properties. We show that these procedures preserve the distribution function if the imputation model is well specified. The results of a simulation study illustrate the good performance of the proposed methods in terms of bias and mean square error.
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