effect_counts_items_grouped: Effect size and test for comparing multiple variables by a...

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

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

Description

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

Usage

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

Arguments

data	A tibble containing item measures and grouping variable.
cols	Tidyselect item variables (e.g. starts_with...).
cross	The column holding groups to compare.
method	The output metrics, currently only cramer is supported.
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_items_grouped(
  data, starts_with("cg_adoption_adv"),  sd_gender
)

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