期刊
BIOMETRIKA
卷 98, 期 1, 页码 119-132出版社
OXFORD UNIV PRESS
DOI: 10.1093/biomet/asq073
关键词
em algorithm; Importance sampling; Item nonresponse; Monte Carlo EM; Multiple imputation
资金
- US Department of Agriculture Natural Resources Conservation Service
- Iowa State University
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.
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