Bayes Factor

Definition: A continuous statistical measure for model selection used in Bayesian inference, describing the relative evidence for one model over another, regardless of whether the models are correct. Bayes factors (BF) range from 0 to infinity, indicating the relative strength of the evidence, and where 1 is a neutral point of no evidence. In contrast to p-values, Bayes factors allow for 3 types of conclusions: a) evidence for the alternative hypothesis, b) evidence for the null hypothesis, and c) no sufficient evidence for either. Thus, BF are typically expressed as BF10 for evidence regarding the alternative compared to the null hypothesis, and as BF01 for evidence regarding the null compared to the alternative hypothesis.

Related terms: <a href='/glossary/bayesian-inference/'>Bayesian inference</a>, Bayesian statistics, <a href='/glossary/likelihood-function/'>Likelihood function</a>, Null Hypothesis Significance Testing (NHST), <a href='/glossary/p-value/'>p-value</a>

Reference: Hoijtink et al. (2019) Makowski et al. (2019)

Drafted and Reviewed by: Meng Liu, Alaa AlDoh, Helena Hartmann, Connor Keating, Kai Krautter, Michele C. Lim, Suzanne L. K. Stewart, Ana Todorovic

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