heteroscedasticity_test: Test for heteroscedasticity in AOV models

In bayesics: Bayesian Analyses for One- and Two-Sample Inference and Regression Methods

Test for heteroscedasticity in AOV models

Description

Use Chib's method to compute the Bayes factor to test for heteroscedasticity in analysis of variance models.

Usage

heteroscedasticity_test(hetero_model, homo_model)

Arguments

hetero_model	aov_b object where the heteroscedastic argument has been set to TRUE (the default)
homo_model	aov_b object where the heteroscedastic argument has been set to FALSE

Value

(returned invisible) A tibble with Bayes factors and interpretations.

References

Kass, R. E., & Raftery, A. E. (1995). Bayes Factors. Journal of the American Statistical Association, 90(430), 773–795.

Examples

# Test homoscedastic case
## Generate some data
set.seed(2025)
N = 200
test_data = 
  data.frame(x1 = rep(letters[1:5],N/5))
test_data$outcome = 
  rnorm(N,-1 + 2 * (test_data$x1 %in% c("d","e")) )

## Fit the anova models
hetero_model = 
  aov_b(outcome ~ x1,
        test_data)
homo_model = 
  aov_b(outcome ~ x1,
        test_data,
        heteroscedastic = FALSE)

## Perform test for heteroscedasticity using Bayes factors
heteroscedasticity_test(hetero_model,
                        homo_model)

# Test heteroscedastic case
## Generate some data
set.seed(2025)
N = 200
test_data = 
  data.frame(x1 = rep(letters[1:5],N/5))
test_data$outcome = 
  rnorm(N,
        -1 + 2 * (test_data$x1 %in% c("d","e")),
        sd = 3 - 2 * (test_data$x1 %in% c("d","e")))

## Fit the anova models
hetero_model = 
  aov_b(outcome ~ x1,
        test_data)
homo_model = 
  aov_b(outcome ~ x1,
        test_data,
        heteroscedastic = FALSE)

## Perform test for heteroscedasticity using Bayes factors
heteroscedasticity_test(hetero_model,
                        homo_model)

bayesics documentation built on March 11, 2026, 5:07 p.m.