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Multiple Imputation of Missing Data Using Stata
dss.princeton.eduMultiple imputation (MI) is a statistical technique for dealing with missing data. In MI the distribution of observed data is used to estimate a set of plausible values for missing data. The missing values are replaced by the estimated plausible values to create a “complete” dataset.
Dealing with missing data: Key assumptions and methods for ...
www.bu.edumodel using weighted least squares or generalized least squares leads to better results (Graham, 2009) (Allison, 2001) and (Briggs et al., 2003). Limitations of imputation techniques in general: They lead to an underestimation of standard …