VIM: matchImpute – R documentation

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matchImpute

Fast matching/imputation based on categorical variable

Description

Suitable donors are searched based on matching of the categorical variables. The variables are dropped in reversed order, so that the last element of 'match_var' is dropped first and the first element of the vector is dropped last.

Usage

matchImpute(
  data,
  variable = colnames(data)[!colnames(data) %in% match_var],
  match_var,
  imp_var = TRUE,
  imp_suffix = "imp"
)

Arguments

`data`	data.frame, data.table or matrix
`variable`	variables to be imputed
`match_var`	variables used for matching
`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

Details

The method works by sampling values from the suitable donors.

Value

the imputed data set.

Author(s)

Johannes Gussenbauer, Alexander Kowarik

Examples

data(sleep,package="VIM")
imp_data <- matchImpute(sleep,variable=c("NonD","Dream","Sleep","Span","Gest"),
  match_var=c("Exp","Danger"))

data(testdata,package="VIM")
imp_testdata1 <- matchImpute(testdata$wna,match_var=c("c1","c2","b1","b2"))

dt <- data.table::data.table(testdata$wna)
imp_testdata2 <- matchImpute(dt,match_var=c("c1","c2","b1","b2"))

VIM

Visualization and Imputation of Missing Values

v6.1.0

GPL (>= 2)

Authors

Matthias Templ [aut, cre], Alexander Kowarik [aut] (<https://orcid.org/0000-0001-8598-4130>), Andreas Alfons [aut], Gregor de Cillia [aut], Bernd Prantner [ctb], Wolfgang Rannetbauer [aut]

Initial release