volker (version 3.2.0)

effect_counts_items_grouped: 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,
  ...
)

Value

A volker tibble.

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.

Examples

library(volker)
data <- volker::chatgpt

effect_counts_items_grouped(
  data, starts_with("cg_adoption_adv"),  sd_gender
)