Hot Deck imputation for multivariate missing data
نویسندگان
چکیده
Fractional hot deck imputation, considered in Fuller and Kim (2005), is extended to multivariate missing data. The joint distribution of the study items is nonparametrically estimated using a discrete approximation, where the discrete transformation also serves to define imputation cells. The procedure first estimates the probabilities for the cells and then imputes real observations for missing items. Calibration weighting is used to reduce the imputation variance. Replication variance estimation is discussed.
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