The use of multiple imputation for the analysis of missing data.

@article{Sinharay2001TheUO,
  title={The use of multiple imputation for the analysis of missing data.},
  author={Sandip Sinharay and Hal S. Stern and Debby Russell},
  journal={Psychological methods},
  year={2001},
  volume={6 4},
  pages={
          317-29
        }
}
This article provides a comprehensive review of multiple imputation (MI), a technique for analyzing data sets with missing values. Formally, MI is the process of replacing each missing data point with a set of m > 1 plausible values to generate m complete data sets. These complete data sets are then analyzed by standard statistical software, and the results combined, to give parameter estimates and standard errors that take into account the uncertainty due to the missing data values. This… CONTINUE READING

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