effect_metrics_items_cor_items: Output correlation coefficients for multiple items

In volker: High-Level Functions for Tabulating, Charting and Reporting Survey Data

Output correlation coefficients for multiple items

Description

The correlation is calculated using stats::cor.test.

Usage

effect_metrics_items_cor_items(
  data,
  cols,
  cross,
  method = "pearson",
  labels = TRUE,
  clean = TRUE,
  ...
)

Arguments

data	A tibble containing item measures.
cols	Tidyselect item variables (e.g. starts_with...).
cross	Tidyselect item variables (e.g. starts_with...).
method	The output metrics, pearson = Pearson's R, spearman = Spearman's rho.
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_metrics.

Value

A volker table containing correlations.

If method = "pearson":

• R-squared: Coefficient of determination.

• n: Number of cases the calculation is based on.

• Pearson's r: Correlation coefficient.

• ci low / ci high: Lower and upper bounds of the 95% confidence interval.

• df: Degrees of freedom.

• t: t-statistic.

• p: p-value for the statistical test, indicating whether the correlation differs from zero.

• stars: Significance stars based on the p-value (*, **, ***).

If method = "spearman":

• Spearman's rho is displayed instead of Pearson's r.

• S-statistic is used instead of the t-statistic.

Examples

library(volker)
data <- volker::chatgpt

effect_metrics_items_cor_items(
  data,
  starts_with("cg_adoption_adv"),
  starts_with("use"),
  metric = TRUE
)

volker documentation built on April 12, 2025, 9:16 a.m.