Sensitivity analysis after multiple imputation under missing at random: a weighting approach.

@article{Carpenter2007SensitivityAA,
  title={Sensitivity analysis after multiple imputation under missing at random: a weighting approach.},
  author={James R. Carpenter and Michael G. Kenward and Ian R. White},
  journal={Statistical methods in medical research},
  year={2007},
  volume={16 3},
  pages={259-75}
}
Multiple imputation (MI) is now well established as a flexible, general, method for the analysis of data sets with missing values. Most implementations assume the missing data are ;missing at random' (MAR), that is, given the observed data, the reason for the missing data does not depend on the unseen data. However, although this is a helpful and simplifying working assumption, it is unlikely to be true in practice. Assessing the sensitivity of the analysis to the MAR assumption is therefore… CONTINUE READING
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