Output test statistics and effect size for contingency tables — effect_counts_one

Chi squared is calculated using stats::chisq.test. If any cell contains less than 5 observations, the exact-parameter is set.

Usage

effect_counts_one_grouped(data, col, cross, clean = TRUE, ...)

Arguments

data: A tibble.
col: The column holding factor values.
cross: The column holding groups to compare.
clean: Prepare data by data_clean.
...: Placeholder to allow calling the method with unused parameters from effect_counts.

Value

A volker tibble with the following statistical measures:

Cramer's V: Effect size measuring the association between two variables.
n: Number of cases the calculation is based on.
Chi-squared: Chi-Squared test statistic.
df: Degrees of freedom.
p: p-value for the statistical test.
stars: Significance stars based on p-value (*, **, ***).

Details

Phi is derived from the Chi squared value by sqrt(fit$statistic / n). Cramer's V is derived by sqrt(phi / (min(dim(contingency)[1], dim(contingency)[2]) - 1)).

Examples

library(volker)
data <- volker::chatgpt

effect_counts_one_grouped(data, adopter, sd_gender)
#> 
#> 
#> |Statistic   | Value|
#> |:-----------|-----:|
#> |Cramer's V  |  0.26|
#> |n           |   101|
#> |Chi-squared | 13.48|
#> |df          |      |
#> |p           | 0.016|
#> |stars       |     *|