effect_counts_items_grouped_items: Effect size and test for comparing multiple variables by...

In volker: High-Level Functions for Tabulating, Charting and Reporting Survey Data

Effect size and test for comparing multiple variables by multiple grouping variables

Description

Effect size and test for comparing multiple variables by multiple grouping variables

Usage

effect_counts_items_grouped_items(
  data,
  cols,
  cross,
  method = "cramer",
  adjust = "fdr",
  category = NULL,
  labels = TRUE,
  clean = TRUE,
  ...
)

Arguments

data	A tibble containing item measures and grouping variable.
cols	Tidyselect item variables (e.g. starts_with...).
cross	The columns holding groups to compare.
method	The output metrics: cramer = Cramer's V, pmi = Pointwise Mutual Information, npmi = Normalized PMI.
adjust	Performing multiple significance tests inflates the alpha error. Thus, p values need to be adjusted according to the number of tests. Set a method supported by stats::p.adjust, e.g. "fdr" (the default) or "bonferroni". Disable adjustment with FALSE.
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 effect_counts.

Value

A volker tibble.

Examples

library(volker)
data <- volker::chatgpt

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

volker documentation built on Nov. 5, 2025, 5:21 p.m.