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.
Copyright Owner
Biometrika Trust
Copyright Date
2011
Language
en
File Format
application/pdf
Recommended Citation
Kim, Jae Kwang, "Parametric fractional imputation for missing data analysis" (2011). Statistics Publications. 102.
https://lib.dr.iastate.edu/stat_las_pubs/102
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.