#' Calculate the totals over an imputed dataset
#' @param data the orginal dataset with missing values
#' @param imputations the multiple imputations generated by e.g. \code{\link{imputeINLA}}
#' @param variable the name of the variable for which the imputations are calculated
#' @param rhs the right hand side of the formula for the aggregation
#' @return a dataset containing the totals for each imputations. The first few columns will contains the \code{rhs} variables.
#' @template deprecated
#' @export
imputedTotals <- function(data, imputations, variable, rhs){
#nocov start
.Deprecated(
new = "aggregate_impute"
)
totals <- lapply(seq_len(ncol(imputations)), function(i){
data[, variable][is.na(data[, variable])] <- imputations[, i]
aggregate(
as.formula(paste(variable, rhs, sep = "~")),
data = data,
FUN = sum
)
})
rhs <- totals[[1]][, -ncol(totals[[1]])]
totals <- sapply(totals, function(x){
x[, ncol(x)]
})
colnames(totals) <- sprintf(
paste(
"Imputation%0",
ceiling(log10(ncol(totals))),
"i",
sep = ""
),
seq_len(ncol(totals))
)
cbind(
rhs,
totals
)
# nocov end
}
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