summary: Summary functions for bayesics objects

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

Summary functions for bayesics objects

Description

Summary functions for bayesics objects

Usage

## S3 method for class 'lm_b'
summary(object, CI_level = 0.95, ...)

## S3 method for class 'aov_b'
summary(object, CI_level = 0.95, ...)

## S3 method for class 'np_glm_b'
summary(object, CI_level = 0.95, interpretable_scale = TRUE, ...)

## S3 method for class 'lm_b_bma'
summary(object, CI_level = 0.95, ...)

## S3 method for class 'glm_b'
summary(object, CI_level = 0.95, interpretable_scale = TRUE, ...)

## S3 method for class 'mediate_b'
summary(object, CI_level = 0.95, ...)

Arguments

object	bayesics object
CI_level	Posterior probability covered by credible interval
...	optional arguments.
interpretable_scale	ADD description!

Value

tibble with summary values

Examples

set.seed(2025)
N = 500
test_data <-
  data.frame(x1 = rnorm(N),
             x2 = rnorm(N),
             x3 = letters[1:5])
test_data$outcome <-
  rnorm(N,-1 + test_data$x1 + 2 * (test_data$x3 %in% c("d","e")) )
fit1 <-
  lm_b(outcome ~ x1 + x2 + x3,
       data = test_data)
summary(fit1)

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