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_")
)
#> 
#> 
#> |Expectations                             |                   Usage| Cramer's V| Chi-squared|  n| df|     p| stars|
#> |:----------------------------------------|-----------------------:|----------:|-----------:|--:|--:|-----:|-----:|
#> |ChatGPT has clear advantages compared... |      in private context|       0.32|       41.27| 99|   | 0.006|    **|
#> |ChatGPT has clear advantages compared... | in professional context|       0.24|       23.46| 99|   | 0.114|      |
#> |Using ChatGPT brings financial benefits. |      in private context|       0.24|       22.48| 99|   | 0.135|      |
#> |Using ChatGPT brings financial benefits. | in professional context|       0.37|       53.99| 99|   | 0.004|    **|
#> |Using ChatGPT is advantageous in many... |      in private context|       0.25|       24.15| 99|   | 0.114|      |
#> |Using ChatGPT is advantageous in many... | in professional context|       0.30|       34.57| 99|   | 0.019|     *|
#> |Compared to other systems, using Chat... |      in private context|       0.30|       34.62| 99|   | 0.021|     *|
#> |Compared to other systems, using Chat... | in professional context|       0.20|       16.23| 99|   | 0.441|      |
#> 
#> n=99. 2 missing case(s) omitted. Adjusted significance p values with fdr method.
#>