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Convert BIC indices to Bayes Factors via the BIC-approximation method.

Source: R/bic_to_bf.R
bic_to_bf.Rd

The difference between two Bayesian information criterion (BIC) indices of two models can be used to approximate Bayes factors via:
$$BF_{10} = e^{(BIC_0 - BIC_1)/2}$$

Usage

bic_to_bf(bic, denominator, log = FALSE)

Arguments

bic

A vector of BIC values.

denominator

The BIC value to use as a denominator (to test against).

log

If TRUE, return the log(BF).

Value

The Bayes Factors corresponding to the BIC values against the denominator.

References

Wagenmakers, E. J. (2007). A practical solution to the pervasive problems of p values. Psychonomic bulletin & review, 14(5), 779-804

Examples

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)
#> [1] 1.000000e+00 1.695852e+29 5.843105e+55 2.203243e+54