James Carpenter|Michael G. Kenward|Stijn Vansteelandt
A Comparison of Multiple Imputation and Doubly Robust Estimation for Analyses with Missing Data
London School of Hygiene & Tropical Medicine|London School of Hygiene & Tropical Medicine|Ghent University Hospital
summary multiple imputation wellestablished technique analysing data sets units incomplete observations provided imputation model correct resulting estimates consistent alternative weighting inverse probability observing complete data unit conceptually simple involves fewer modelling assumptions known inefficient relative fully parametric approach sensitive choice weighting model last decade considerable body theoretical work improve performance inverse probability weighting leading development doubly robust doubly protected estimators present intuitive review developments contrast estimators multiple imputation theoretical practical viewpoint