Correlation of categorical items with categorical items

Usage

plot_counts_items_grouped_items(
  data,
  cols,
  cross,
  method = "cramer",
  numbers = TRUE,
  category = NULL,
  title = TRUE,
  labels = TRUE,
  clean = TRUE,
  ...
)

Arguments

data

A tibble containing item measures.

cols

Tidyselect item variables (e.g. starts_with...).

cross

Tidyselect item variables (e.g. starts_with...).

method

The method of correlation calculation:

cramer for Cramer's V,
npmi for Normalized Pointwise Mutual Information.

numbers

Whether to print the association values on the tiles. Default is TRUE.

category

The value FALSE will force to plot all categories. A character value will focus a selected category. When NULL, in case of boolean values, only the TRUE category is plotted.

title

If TRUE (default) shows a plot title derived from the column labels. Disable the title with FALSE or provide a custom title as character value.

labels

If TRUE (default) extracts labels from the attributes, see codebook.

clean

Prepare data by data_clean.

...

Placeholder to allow calling the method with unused parameters from plot_counts.

Value

A ggplot object.

Examples

library(volker)
data <- volker::chatgpt

plot_counts_items_grouped_items(
  data,
  starts_with("cg_adoption_advantage"),
  starts_with("cg_adoption_fearofuse"),
  method = "cramer"
)