Performs a goodness-of-fit test and calculates the Gini coefficient for each item.
The goodness-of-fit-test is calculated using stats::chisq.test.
Arguments
- data
A tibble containing item measures.
- cols
Tidyselect item variables (e.g. starts_with...).
- 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(data, starts_with("cg_adoption_adv"))
#>
#>
#> |Expectations | Gini| Number of cases| Chi-squared| p value| stars|
#> |:-----------------------------------------------------------|----:|---------------:|-----------:|-------:|-----:|
#> |ChatGPT has clear advantages compared to similar offerings. | 0.36| 99| 43.5| 0| ***|
#> |Using ChatGPT brings financial benefits. | 0.19| 99| 14.3| 0| **|
#> |Using ChatGPT is advantageous in many tasks. | 0.36| 99| 47.0| 0| ***|
#> |Compared to other systems, using ChatGPT is more fun. | 0.40| 99| 53.7| 0| ***|
#>
#> 2 missing case(s) omitted.
#>