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Tip revision: 428249f43a9c6fd0c425b28deb5fee51a9525d69 authored by Dominique Makowski on 18 September 2022, 01:46:03 UTC
version 0.13.0
Tip revision: 428249f
% 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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