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Bar plots for multiply imputed values for a single factor variable

Source: R/plot_1var.R
plot_bar.Rd

Plot bar plots of observed values versus m sets of imputed values for a specified factor variable using ggplot2.

Usage

plot_bar(
  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

var.name

The name of a factor variable of interest

original.data

The original data with missing data

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

Bar plots for a factor variable

Examples

# create some extra missing values in a factor variable "HSSEX" (originally fully observed)
nhanes3_NA <- createNA(nhanes3, var.names = "HSSEX", p = 0.1)

# obtain m multiply datasets
params <- list(max_depth = 3, subsample = 0.8, nthread = 2)
imputed.data <- mixgb(data = nhanes3_NA, m = 3, xgb.params = params, nrounds = 30)

# plot the multiply imputed values for variable "HSSEX"
plot_bar(
  imputation.list = imputed.data, var.name = "HSSEX",
  original.data = nhanes3_NA
)