Histogram with density plots for multiply imputed values for a single numeric variable

Plot histograms with density curves of observed values versus m sets of imputed values for a specified numeric variable using ggplot2.

Usage

plot_hist(
  imputation.list,
  var.name,
  original.data,
  true.data = NULL,
  color.pal = NULL
)

Arguments

imputation.list

A list of m imputed datasets returned by the mixgb imputer, or other package.

var.name

The name of a numeric variable of interest.

original.data

The original data with missing values.

true.data

The true data without missing values. This is generally unknown in practice. If the true data is known (e.g., in cases where it is generated by simulation), it can be specified in this argument. The output will then have an extra panel called MaskedTrue, which shows values originally observed but intentionally made missing.

color.pal

A vector of hex color codes for the observed and m sets of imputed values panels. The vector should be of length m+1. Default: NULL (use "gray40" for the observed panel, use ggplot2 default colors for other panels.)

Value

Histogram with density plots

Examples

# obtain m multiply datasets
params <- list(max_depth = 3, subsample = 0.8, nthread = 2)
imputed.data <- mixgb(data = nhanes3, m = 3, xgb.params = params, nrounds = 30)

# plot the multiply imputed values for variable "BMPHEAD"
plot_hist(
  imputation.list = imputed.data, var.name = "BMPHEAD",
  original.data = nhanes3
)