Multiple imputation: Theory and method

被引：0
作者：
Zhang, P [1 ]
机构：
[1] Pfizer Consumer Healthcare, Morris Plains, NJ 07950 USA
来源：
INTERNATIONAL STATISTICAL REVIEW | 2003年 / 71卷 / 03期
关键词：
missing data; incomplete data; missingness mechanism; multiple imputation;
D O I：
暂无
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In this review paper, we discuss the theoretical background of multiple imputation, describe how to build an imputation model and how to create proper imputations. We also present the rules for making repeated imputation inferences. Three widely used multiple imputation methods, the propensity score method, the predictive model method and the Markov chain Monte Carlo (MCMC) method, are presented and discussed.
引用
收藏
页码：581 / 592
页数：12
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