% Generated by roxygen2: do not edit by hand % Please edit documentation in R/bayesfactor.R \name{bayesfactor} \alias{bayesfactor} \title{Bayes Factors (BF)} \usage{ bayesfactor( ..., prior = NULL, direction = "two-sided", null = 0, hypothesis = NULL, effects = c("fixed", "random", "all"), verbose = TRUE, denominator = 1, match_models = FALSE, prior_odds = NULL ) } \arguments{ \item{...}{A numeric vector, model object(s), or the output from \code{bayesfactor_models}.} \item{prior}{An object representing a prior distribution (see 'Details').} \item{direction}{Test type (see 'Details'). One of \code{0}, \code{"two-sided"} (default, two tailed), \code{-1}, \code{"left"} (left tailed) or \code{1}, \code{"right"} (right tailed).} \item{null}{Value of the null, either a scaler (for point-null) or a a range (for a interval-null).} \item{hypothesis}{A character vector specifying the restrictions as logical conditions (see examples below).} \item{effects}{Should results for fixed effects, random effects or both be returned? Only applies to mixed models. May be abbreviated.} \item{verbose}{Toggle off warnings.} \item{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 \code{BFBayesFactor}.} \item{match_models}{See details.} \item{prior_odds}{Optional vector of prior odds for the models. See \code{BayesFactor::priorOdds<-}.} } \value{ Some type of Bayes factor, depending on the input. See \code{\link{bayesfactor_parameters}}, \code{\link{bayesfactor_models}} or \code{\link{bayesfactor_inclusion}} } \description{ This function compte the Bayes factors (BFs) that are appropriate to the input. For vectors or single models, it will compute \code{\link[=bayesfactor_parameters]{BFs for single parameters}}, or is \code{hypothesis} is specified, \code{\link[=bayesfactor_restricted]{BFs for restricted models}}. For multiple models, it will return the BF corresponding to \code{\link[=bayesfactor_models]{comparison between models}} and if a model comparison is passed, it will compute the \code{\link[=bayesfactor_inclusion]{inclusion BF}}. \cr\cr For a complete overview of these functions, read the \href{https://easystats.github.io/bayestestR/articles/bayes_factors.html}{Bayes factor vignette}. } \examples{ library(bayestestR) # Vectors prior <- distribution_normal(1000, mean = 0, sd = 1) posterior <- distribution_normal(1000, mean = .5, sd = .3) bayesfactor(posterior, prior = prior) \dontrun{ # rstanarm models # --------------- if (require("rstanarm")) { model <- stan_lmer(extra ~ group + (1 | ID), data = sleep) bayesfactor(model) } } # 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) }