# Hot-Deck Imputation Implementation of the popular Sequential, Random (within a domain) hot-deck algorithm for imputation. ```r 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 (not overlapping with ord_var) - `ord_var`: variables for sorting the data set before imputation (not overlapping with variable) - `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 as character string. e.g. ">5" or c(">5","<10). If the list element for a variable is NULL no condition will be applied for this variable. - `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 ## Returns the imputed data set. ## Note If the sequential hotdeck does not lead to a suitable, a random donor in the group will be used. ## Examples ```r data(sleep) sleepI <- hotdeck(sleep) sleepI2 <- hotdeck(sleep,ord_var="BodyWgt",domain_var="Pred") # Usage of donorcond in a simple example sleepI3 <- hotdeck( sleep, variable = c("NonD", "Dream", "Sleep", "Span", "Gest"), ord_var = "BodyWgt", domain_var = "Pred", donorcond = list(">4", "<17", ">1.5", "%between%c(8,13)", ">5") ) 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") ``` ## References A. Kowarik, M. Templ (2016) Imputation with R package VIM. **Journal of Statistical Software**, 74(7), 1-16. ## See Also Other imputation methods: `impPCA()`, `irmi()`, `kNN()`, `matchImpute()`, `medianSamp()`, `rangerImpute()`, `regressionImp()`, `sampleCat()` ## Author(s) Alexander Kowarik

hotdeck function