compare_imp: Comparing imputations and original data distributions

In miceFast: Fast Imputations Using 'Rcpp' and 'Armadillo'

Comparing imputations and original data distributions

Description

ggplot2 visualization to support which imputation method to choose

Usage

compare_imp(df, origin, target)

Arguments

df	data.frame with origin variable and the new one with imputations
origin	character value - the name of origin variable with values before any imputations
target	character vector - names of variables with applied imputations

Value

ggplot2 object

Examples

library(miceFast)
library(ggplot2)
data(air_miss)
air_miss$Ozone_imp <- fill_NA(
  x = air_miss,
  model = "lm_bayes",
  posit_y = 1,
  posit_x = c(4, 6),
  logreg = TRUE
)
air_miss$Ozone_imp2 <- fill_NA_N(
  x = air_miss,
  model = "pmm",
  posit_y = 1,
  posit_x = c(4, 6),
  logreg = TRUE
)

compare_imp(air_miss, origin = "Ozone", "Ozone_imp")
compare_imp(air_miss, origin = "Ozone", c("Ozone_imp", "Ozone_imp2"))

miceFast documentation built on Nov. 18, 2022, 1:07 a.m.