Imputation by classification and regression trees

Apply imputation to the data by classification and regression trees (Breiman et al. 1984; Doove et al. 2014; van Buuren 2018) .

Usage

impute.mice_cart(dataSet, m = 5, seed = 362436069)

Arguments

dataSet

A data frame containing the data signals.

m

An integer (default = 5) specifying the number of multiple imputations.

seed

An integer (default = 362436069) specifying the seed used for the random number generator for reproducibility.

Value

The imputed data.

References

Breiman L, Friedman J, Olshen RA, Stone CJ (1984). Classification and Regression Trees. Routledge, New York, NY, USA. ISBN 9780412048418.

Doove LL, van Buuren S, Dusseldorp E (2014). “Recursive Partitioning for Missing Data Imputation in the Presence of Interaction Effects.” Computational Statistics & Data Analysis, 72, 92–104. doi:10.1016/j.csda.2013.10.025 .

van Buuren S (2018). Flexible Imputation of Missing Data. Chapman \& Hall/CRC, New York, NY, USA. ISBN 9781032178639.