Summarise what was imputed, across the m completed datasets — summary.hvti_imputation

Reduces the record to a per-variable table: which method each variable was imputed with, and how many of its values were filled. Unlike summary.hvti_imputation(), there is no single fill_value column – each of the m draws can fill a given cell with a different value, which is the entire point of multiple imputation, so no single value speaks for all of them.

Usage

# S3 method for class 'hvti_imputation_multi'
summary(object, ...)

Arguments

object: An object of class hvti_imputation_multi.
...: Ignored.

Value

A data frame with one row per imputed variable: the variable name, the method used, the number of values filled, and the proportion of rows that is.

Examples

set.seed(42)
n <- 30
dat <- data.frame(
  age = round(rnorm(n, 60, 8)),
  grp = factor(sample(c("a", "b", "c"), n, replace = TRUE))
)
dat$age[sample(n, 4)] <- NA
dat$grp[sample(n, 4)] <- NA

out <- impute_multiple(dat, vars = c("age", "grp"), m = 2, maxit = 2,
                       seed = 1)
summary(out)
#>   variable  method n_imputed prop_imputed
#> 1      age     pmm         4    0.1333333
#> 2      grp polyreg         4    0.1333333