Accounting for Non-ignorable Sampling and Non-response in Statistical Matching

IF 1.7 3区 数学 Q1 STATISTICS & PROBABILITY
Daniela Marella, Danny Pfeffermann
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引用次数: 1

Abstract

Data for statistical analysis is often available from different samples, with each sample containing measurements on only some of the variables of interest. Statistical matching attempts to generate a fused database containing matched measurements on all the target variables. In this article, we consider the use of statistical matching when the samples are drawn by informative sampling designs and are subject to not missing at random non-response. The problem with ignoring the sampling process and non-response is that the distribution of the data observed for the responding units can be very different from the distribution holding for the population data, which may distort the inference process and result in a matched database that misrepresents the joint distribution in the population. Our proposed methodology employs the empirical likelihood approach and is shown to perform well in a simulation experiment and when applied to real sample data.

Abstract Image

统计匹配中不可忽略抽样和无响应的解释
用于统计分析的数据通常来自不同的样本,每个样本只包含对感兴趣的一些变量的测量。统计匹配尝试生成包含所有目标变量的匹配测量的融合数据库。在这篇文章中,当样本是通过信息采样设计绘制的,并且在随机无响应时不会丢失时,我们考虑使用统计匹配。忽略采样过程和非响应的问题是,响应单元观测到的数据分布可能与总体数据的分布非常不同,这可能会扭曲推理过程,并导致匹配的数据库歪曲总体中的联合分布。我们提出的方法采用了经验似然法,并在模拟实验中和应用于真实样本数据时表现良好。
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来源期刊
International Statistical Review
International Statistical Review 数学-统计学与概率论
CiteScore
4.30
自引率
5.00%
发文量
52
审稿时长
>12 weeks
期刊介绍: International Statistical Review is the flagship journal of the International Statistical Institute (ISI) and of its family of Associations. It publishes papers of broad and general interest in statistics and probability. The term Review is to be interpreted broadly. The types of papers that are suitable for publication include (but are not limited to) the following: reviews/surveys of significant developments in theory, methodology, statistical computing and graphics, statistical education, and application areas; tutorials on important topics; expository papers on emerging areas of research or application; papers describing new developments and/or challenges in relevant areas; papers addressing foundational issues; papers on the history of statistics and probability; white papers on topics of importance to the profession or society; and historical assessment of seminal papers in the field and their impact.
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