VIM (version 4.6.0)

hotdeck: Hot-Deck Imputation

Description

Implementation of the popular Sequential, Random (within a domain) hot-deck algorithm for imputation.

Usage

hotdeck(data, variable = NULL, ord_var = NULL, domain_var = NULL, makeNA = NULL, NAcond = NULL, impNA = TRUE, donorcond = NULL, imp_var = TRUE, imp_suffix = "imp")

Arguments

data

data.frame or matrix

variable

variables where missing values should be imputed

ord_var

variables for sorting the data set before imputation

domain_var

variables for building domains and impute within these domains

makeNA

list of length equal to the number of variables, with values, that should be converted to NA for each variable

NAcond

list of length equal to the number of variables, with a condition for imputing a NA

impNA

TRUE/FALSE whether NA should be imputed

donorcond

list of length equal to the number of variables, with a donorcond condition for the donors e.g. ">5"

imp_var

TRUE/FALSE if a TRUE/FALSE variables for each imputed variable should be created show the imputation status

imp_suffix

suffix for the TRUE/FALSE variables showing the imputation status

Value

the imputed data set.

References

A. Kowarik, M. Templ (2016) Imputation with R package VIM. Journal of Statistical Software, 74(7), 1-16.

Examples

data(sleep)
sleepI <- hotdeck(sleep)
sleepI2 <- hotdeck(sleep,ord_var="BodyWgt",domain_var="Pred")

set.seed(132)
nRows <- 1e3
# Generate a data set with nRows rows and several variables
x<-data.frame(x=rnorm(nRows),y=rnorm(nRows),z=sample(LETTERS,nRows,replace=TRUE),
    d1=sample(LETTERS[1:3],nRows,replace=TRUE),d2=sample(LETTERS[1:2],nRows,replace=TRUE),
    o1=rnorm(nRows),o2=rnorm(nRows),o3=rnorm(100))
origX <- x
x[sample(1:nRows,nRows/10),1] <- NA
x[sample(1:nRows,nRows/10),2] <- NA
x[sample(1:nRows,nRows/10),3] <- NA
x[sample(1:nRows,nRows/10),4] <- NA
xImp <- hotdeck(x,ord_var = c("o1","o2","o3"),domain_var="d2")