Missing-Data Adjustments in Large Surveys
讨论了大型政府调查中数值数据通用插补方法的有用性质，提出基于预测均值匹配的插补方法，并探讨了加权调整的优缺点。
Useful properties of a general-purpose imputation method for numerical data are suggested and discussed in the context of several large government surveys. Imputation based on predictive mean matching is proposed as a useful extension of methods in existing practice, and versions of the method are presented for unit nonresponse and item nonresponse with a general pattern of missingness. Extensions of the method to provide multiple imputations are also considered. Pros and cons of weighting adjustments are discussed, and weighting-based analogs to predictive mean matching are outlined.