effect_metrics_one_grouped: Output a regression table with estimates and macro statistics

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

Output a regression table with estimates and macro statistics

Description

The regression output comes from stats::lm. T-test is performed using stats::t.test. Normality check is performed using stats::shapiro.test. Equality of variances across groups is assessed using car::leveneTest. Cohen's d is calculated using effectsize::cohens_d.

Usage

effect_metrics_one_grouped(
  data,
  col,
  cross,
  method = "lm",
  labels = TRUE,
  clean = TRUE,
  ...
)

Arguments

data	A tibble.
col	The column holding metric values.
cross	The column holding groups to compare.
method	A character vector of methods, e.g. c("t.test","lm"). Supported methods are t.test (only valid if the cross column contains two levels) and lm (regression results).
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 list object containing volker tables with the requested statistics.

Regression table:

• estimate: Regression coefficient (unstandardized).

• ci low / ci high: lower and upper bound of the 95% confidence interval.

• se: Standard error of the estimate.

• t: t-statistic.

• p: p-value for the statistical test.

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

Macro statistics:

• Adjusted R-squared: Adjusted coefficient of determination.

• F: F-statistic for the overall significance of the model.

• df: Degrees of freedom for the model.

• residual df: Residual degrees of freedom.

• p: p-value for the statistical test.

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

If method = t.test:

Shapiro-Wilk test (normality check):

• W: W-statistic from the Shapiro-Wilk normality test.

• p: p-value for the test.

• normality: Interpretation of the Shapiro-Wilk test.

Levene test (equality of variances):

• F: F-statistic from the Levene test for equality of variances between groups.

• p: p-value for Levene's test.

• variances: Interpretation of the Levene test.

Cohen's d (effect size):

• d: Standardized mean difference between the two groups.

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

t-test

• method: Type of t-test performed (e.g., "Two Sample t-test").

• difference: Observed difference between group means.

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

• se: Estimated standard error of the difference.

• df: Degrees of freedom used in the t-test.

• t: t-statistic.

• p: p-value for the t-test.

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

Examples

library(volker)
data <- volker::chatgpt

effect_metrics_one_grouped(data, sd_age, sd_gender)

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