A common misconception of missing data methods is the assumption that imputed values should represent "real" values. The purpose when addressing missing data is to correctly reproduce the variance/covariance matrix we would have observed had our data not had any missing information.
http://www.ats.ucla.edu/stat/stata/seminars/missing_data/Multiple_imputation/mi_in_stata_pt1_new.htm
