Inference for imputation estimators

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 t...

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Bibliographic Details
Published in:Biometrika 2000-03, Vol.87 (1), p.113-124
Main Authors: Robins, JM, Wang, N
Format: Article
Language:English
Subjects:
Analytical estimating
Asymptotic variance
Confidence intervals
Consistent estimators
Data imputation
Datasets
Estimation bias
Estimators
Exact sciences and technology
Influence function
Mathematics
Missing data
Modeling
Parametric inference
Parametric models
Probability and statistics
Sciences and techniques of general use
Software packages
Statistical variance
Statistics
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Summary: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.
ISSN:0006-3444
1464-3510
DOI:10.1093/biomet/87.1.113