
Effect size and test for comparing multiple variables by multiple grouping variables
Source:R/effects.R
effect_counts_items_grouped_items.Rd
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.
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.
#>