Inference for imputation estimators

• 成果类型: Article
• 署名作者: Robins, JM; Wang, NS
• 署名单位: Harvard University; Harvard T.H. Chan School of Public Health; Texas A&M University System; Texas A&M University College Station
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/87.1.113
• 发表日期: 2000
• 页码: 113124
• 关键词: multiple-imputation; Missing Data; uncongenial sources; models; nonresponse; bootstrap; input

摘要

We derive an estimator of the asymptotic variance of both single and multiple imputation estimators. We assume a parametric imputation model but allow for non- and semiparametric analysis models. Our variance estimator, in contrast to the estimator proposed by Rubin (1987), is consistent even when the imputation and analysis models are misspecified and incompatible with one another.