RESULTS: The multiple imputation method imputed missing values of the crossover design and generated valid statistical inferences.
结果：多重填补的方法可用于交叉设计中缺失数据的填补并得出正确的统计推断。
Results The multiple imputation method can impute missing values of the crossover design and generate valid statistical inferences.
结果多重填补的方法可用于交叉设计中缺失数据的填补并得出正确的统计推断。
The topics enclose the important phases of designing a split questionnaire, and the methods of using the multiple imputation method to deal with the missing data.
重点阐述其设计要点，以及如何利用多重插补方法对缺失数据进行处理。
The paper introduces multiple imputation (mi) for missing data in stratified random sampling, and discusses the ordinary method of mi with ignorable nonresponse, and illustrates the essential steps.
介绍分层随机抽样条件下多重插补法处理缺失数据的基本思想，分析可忽略无回答的分层随机抽样建立多重插补的常用方法，并通过实例加以说明。
The paper introduces multiple imputation (mi) for missing data in stratified random sampling, and discusses the ordinary method of mi with ignorable nonresponse, and illustrates the essential steps.
介绍分层随机抽样条件下多重插补法处理缺失数据的基本思想，分析可忽略无回答的分层随机抽样建立多重插补的常用方法，并通过实例加以说明。
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