Heatmap for correlations between multiple items

Usage

plot_metrics_items_cor_items(
  data,
  cols,
  cross,
  method = "pearson",
  numbers = FALSE,
  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 to correlate (e.g. starts_with...).
method: The method of correlation calculation, pearson = Pearson's R, spearman = Spearman's rho.
numbers: Controls whether to display correlation coefficients on the plot.
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_metrics.

Value

A ggplot object.

Examples

library(volker)
data <- volker::chatgpt

plot_metrics_items_cor_items(data, starts_with("cg_adoption_adv"), starts_with("use_"))

#> In the plot, 2 missing case(s) omitted.