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Tip revision: 79b3ea026adbb877bc1921a9cf1ea0eae067cb63 authored by Dominique Makowski on 12 February 2024, 11:40:02 UTC
version 0.13.2
Tip revision: 79b3ea0
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bic_to_bf.R
\title{Convert BIC indices to Bayes Factors via the BIC-approximation method.}
bic_to_bf(bic, denominator, log = FALSE)
\item{bic}{A vector of BIC values.}

\item{denominator}{The BIC value to use as a denominator (to test against).}

\item{log}{If \code{TRUE}, return the \code{log(BF)}.}
The Bayes Factors corresponding to the BIC values against the denominator.
The difference between two Bayesian information criterion (BIC) indices of
two models can be used to approximate Bayes factors via:
\deqn{BF_{10} = e^{(BIC_0 - BIC_1)/2}}{BF10 = exp((BIC0-BIC1)/2)}
bic1 <- BIC(lm(Sepal.Length ~ 1, data = iris))
bic2 <- BIC(lm(Sepal.Length ~ Species, data = iris))
bic3 <- BIC(lm(Sepal.Length ~ Species + Petal.Length, data = iris))
bic4 <- BIC(lm(Sepal.Length ~ Species * Petal.Length, data = iris))

bic_to_bf(c(bic1, bic2, bic3, bic4), denominator = bic1)
Wagenmakers, E. J. (2007). A practical solution to the pervasive problems of
p values. Psychonomic bulletin & review, 14(5), 779-804
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