A note on multiple imputation for method of moments estimation
研究了多重插补在矩估计法中的方差估计问题，指出Rubin方差公式在非顺应条件下存在渐近偏误，并提出基于过度插补的新方差估计量以提供有效推断。
Multiple imputation is widely used for estimation in situations where there are missing data. Rubin (1987) provided an easily applicable formula for multiple imputation variance estimation, but its validity requires the congeniality condition of Meng (1994), which may not be satisfied for method of moments estimation. We give the asymptotic bias of Rubin's variance estimator when method of moments estimation is used in the complete-sample analysis for each imputed dataset. A new variance estimator based on over-imputation is proposed to provide asymptotically valid inference in this case.