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On the bias of the multiple‐imputation variance estimator in survey sampling
Author(s) -
Kim Jae Kwang,
Michael Brick J.,
Fuller Wayne A.,
Kalton Graham
Publication year - 2006
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/j.1467-9868.2006.00546.x
Subject(s) - imputation (statistics) , estimator , statistics , bias of an estimator , variance (accounting) , econometrics , survey sampling , mathematics , minimum variance unbiased estimator , missing data , economics , population , demography , accounting , sociology
Summary. Multiple imputation is a method of estimating the variances of estimators that are constructed with some imputed data. We give an expression for the bias of the multiple‐imputation variance estimator for data that are collected with a complex sample design. The bias may be sizable for certain estimators, such as domain means, when a large fraction of the values are imputed. A bias‐adjusted variance estimator is suggested.