Ignorable and Informative Designs in Survey Sampling Inference
研究了在基于模型的有限总体推断中，样本选择机制的作用，分析了当数据分析师仅掌握部分抽样设计信息时，原本可忽略的设计可能变得具有信息性，并给出了可忽略部分已知设计的条件。
The role of the sample selection mechanism in a model-based approach to finite population inference is examined. When the data analyst has only partial information on the sample design then a design which is ignorable when known fully may become informative. Conditions under which partially known designs can be ignored are established and examined for some standard designs. The results are illustrated by an example used by Scott (1977).