Several Methods of Re-Designing Area Samples Utilizing Probabilities Proportional to Size when the Sizes Change Significantly
规模显著变化时按规模比例概率重设计区域样本的方法AI 解读 ↓
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规模显著变化时按规模比例概率重设计区域样本的方法
- 研究问题
- 当抽样单位增长不均、原有规模度量过时时，如何更新多阶段按规模比例概率的系统抽样，并兼顾无偏性与样本延续？
- 方法与思路
- 作者描述两种修改规模度量的方法，用于单阶段或多阶段系统抽样，并以重复调查背景展示更新前后的样本重叠。
- 材料陈述的贡献
- 摘要称这些方法不引入估计偏差、降低抽取样本量的方差，并在示例中产生不同程度的样本重叠，适合重复调查操作。
- 阅读关注点
- 应核对更新后的选择概率与估计权重、无偏性所针对的估计程序，以及抽取样本量方差和样本重叠的计算方式。
- 阅读边界
- 仅据未注明稿件版本的OpenAlex索引摘要；降低的是抽取样本量方差，不能据此声称所有总体估计量的方差都下降。
原文摘要
For purposes of obtaining statistical data by enumeration, systematic sampling with probability proportional to size in one or more stages is frequently employed. The article describes two methods of changing the measures of sizes without introducing a bias in the estimation procedure. They result in the reduction of the variance of sample take, and, in the illustrative material presented, result in varying degrees of overlap before and after the changes of sizes. These methods are particularly applicable to systematic samples where repetitive panel operations are employed, for example, as in the Canadian Labour Force Survey. In the Canadian Labour Force Survey, a self-weighting sample is selected in two to four stages, often by means of systematic sampling with probability proportional to size, the size being Census or field counts of persons or dwellings. This results in a sample which provides population estimates of employment and unemployment with sufficient accuracy for the cost provided at the provincial and national levels and a sample which can be easily maintained for long periods of time. Unfortunately, the so-called measures of size used in the systematic samples become out of date because of uneven growth in the first stage units. N. Keyfitz [3] and I. P. Fellegi [2] have dealt effectively with methods of adjusting measures of size in the case where one or two units are selected at random without replacement with probability proportional to size so that as few new units need be selected as possible. Other methods of dealing with burgeoning growth have been dealt with by L. Kish [4] and the Bureau of the Census [5].