Boxplots with data points for multiply imputed values for a single numeric variable

Plot boxplots with data points of observed values versus m sets of imputed values for a specified numeric variable using ggplot2.

Usage

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

Arguments

imputation.list

A list of m imputed datasets.

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

Boxplots with data points for a numeric variable

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_box(
  imputation.list = imputed.data, var.name = "BMPHEAD",
  original.data = nhanes3
)