Campus Units

Statistics

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

2011

Journal or Book Title

Biometrika

Volume

98

Issue

1

First Page

119

Last Page

132

DOI

10.1093/biomet/asq073

Abstract

Parametric fractional imputation is proposed as a general tool for missing data analysis. Using fractional weights, the observed likelihood can be approximated by the weighted mean of the imputed data likelihood. Computational efficiency can be achieved using the idea of importance sampling and calibration weighting. The proposed imputation method provides efficient parameter estimates for the model parameters specified in the imputation model and also provides reasonable estimates for parameters that are not part of the imputation model. Variance estimation is discussed and results from a limited simulation study are presented.

Comments

This is a pre-copyedited, author-produced PDF of an article submitted for publication in Biometrika. The version of record (Kim, Jae Kwang. "Parametric fractional imputation for missing data analysis." Biometrika 98, no. 1 (2011): 119-132) is available online at doi:10.1093/biomet/asq073. Posted with permission.

Copyright Owner

Biometrika Trust

Language

en

File Format

application/pdf

Published Version

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