A note on multiple imputation under complex sampling

• 成果类型: Article
• 署名作者: Kim, J. K.; Yang, S.
• 署名单位: Iowa State University; North Carolina State University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asw058
• 发表日期: 2017
• 页码: 221228
• 关键词: POPULATION; MODEL; superpopulation; statistics; inference

摘要

Multiple imputation is popular for handling item nonresponse in survey sampling. Current multiple imputation techniques with complex survey data assume that the sampling design is ignorable. In this paper, we propose a new multiple imputation procedure for parametric inference without this assumption. Instead of using the sample-data likelihood, we use the sampling distribution of the pseudo maximum likelihood estimator to derive the posterior distribution of the parameters. The asymptotic properties of the proposed method are investigated. A simulation study confirms that the new procedure provides unbiased point estimation and valid confidence intervals with correct coverage properties whether or not the sampling design is ignorable.