Bayes Factors (BF)

Source: R/bayesfactor.R

This function compte the Bayes factors (BFs) that are appropriate to the input. For vectors or single models, it will compute BFs for single parameters, or is hypothesis is specified, BFs for restricted models. For multiple models, it will return the BF corresponding to comparison between models and if a model comparison is passed, it will compute the inclusion BF.

For a complete overview of these functions, read the Bayes factor vignette.

bayesfactor(
  ...,
  prior = NULL,
  direction = "two-sided",
  null = 0,
  hypothesis = NULL,
  effects = "fixed",
  verbose = TRUE,
  denominator = 1,
  match_models = FALSE,
  prior_odds = NULL
)

Arguments

...

A numeric vector, model object(s), or the output from bayesfactor_models.

prior

An object representing a prior distribution (see 'Details').

direction

Test type (see 'Details'). One of 0, "two-sided" (default, two tailed), -1, "left" (left tailed) or 1, "right" (right tailed).

null

Value of the null, either a scalar (for point-null) or a range (for a interval-null).

hypothesis

A character vector specifying the restrictions as logical conditions (see examples below).

effects

Should variables for fixed effects ("fixed"), random effects ("random") or both ("all") be returned? Only applies to mixed models. May be abbreviated.

For models of from packages brms or rstanarm there are additional options:

  • "fixed" returns fixed effects.

  • "random_variance" return random effects parameters (variance and correlation components, e.g. those parameters that start with sd_ or cor_).

  • "grouplevel" returns random effects group level estimates, i.e. those parameters that start with r_.

  • "random" returns both "random_variance" and "grouplevel".

  • "all" returns fixed effects and random effects variances.

  • "full" returns all parameters.

verbose

Toggle off warnings.

denominator

Either an integer indicating which of the models to use as the denominator, or a model to be used as a denominator. Ignored for BFBayesFactor.

match_models

See details.

prior_odds

Optional vector of prior odds for the models. See BayesFactor::priorOdds<-.

Value

Some type of Bayes factor, depending on the input. See bayesfactor_parameters(), bayesfactor_models() or bayesfactor_inclusion().

Note

There is also a plot()-method implemented in the see-package.

Examples

if (FALSE) { # \dontrun{
library(bayestestR)

prior <- distribution_normal(1000, mean = 0, sd = 1)
posterior <- distribution_normal(1000, mean = 0.5, sd = 0.3)

bayesfactor(posterior, prior = prior, verbose = FALSE)

# rstanarm models
# ---------------
model <- suppressWarnings(rstanarm::stan_lmer(extra ~ group + (1 | ID), data = sleep))
bayesfactor(model, verbose = FALSE)

# Frequentist models
# ---------------
m0 <- lm(extra ~ 1, data = sleep)
m1 <- lm(extra ~ group, data = sleep)
m2 <- lm(extra ~ group + ID, data = sleep)

comparison <- bayesfactor(m0, m1, m2)
comparison

bayesfactor(comparison)
} # }