create.imputed function

Fills-in missing values in the recipient dataset with values observed on the donors units

Imputes the missing values (NAs) in the recipient dataset with values observed on the donors units after search of donors with NND or random hotdeck.

create.imputed(data.rec, data.don, mtc.ids)

Arguments

• data.rec: A matrix or data frame that has missing values.
• data.don: A matrix or data frame that is used for donation (imputation).
• mtc.ids: A matrix with two columns. Each row must contain the name or the index of the recipient record (row) in data.don and the name or the index of the corresponding donor record (row) in data.don. Note that this type of matrix is returned by the functions NND.hotdeck, RANDwNND.hotdeck, rankNND.hotdeck, and mixed.mtc.

Details

This function allows the missing values (NAs) in the recipient to be filled in with values observed in the donor dataset after searching for donors via NND or random hotdeck using the functions available in the package, i.e. NND.hotdeck, RANDwNND.hotdeck, rankNND.hotdeck, and mixed.mtc. If the same record in the recipient dataset has 2 or more NAs, they will all be replaced with the values observed for that unit on the selected donor; this is equivalent to joint hotdeck imputation.

Returns

The data frame data.rec missing values (NAs) filled in.

References

D'Orazio, M., Di Zio, M. and Scanu, M. (2006). Statistical Matching: Theory and Practice. Wiley, Chichester.

Author(s)

Marcello D'Orazio mdo.statmatch@gmail.com

See Also

NND.hotdeck

RANDwNND.hotdeck

rankNND.hotdeck

Examples

# introduce missing values
# in Petal.Length of iris dataset

set.seed(13579)
pos <- sample(x = 1:nrow(iris), size = 15, 
              replace = FALSE)

iris.rec <- iris[pos, ]  # recipient data.frame with missing values
iris.rec[, "Petal.Length"] <- NA

iris.don <- iris[-pos, ] # donor data.frame ALL observed

# find the closest donors using NND hot deck;
# distances are computed on "Petal.Width"
# donors only of the same Specie

out.NND <- NND.hotdeck(data.rec=iris.rec, data.don=iris.don,
                       match.vars=c("Petal.Width"), 
                       don.class="Species")

# impute missing
iris.rec.imp <- create.imputed(data.rec=iris.rec, data.don=iris.don, 
                        mtc.ids=out.NND$mtc.ids)
summary(iris.rec.imp$Petal.Length)