WebOct 30, 2024 · EJ. November 2024. BF inclusion is similar to a regular BF except that it compares two classes of models, one class with the factor of interest and one without. So you start with prior probabilities on the models; comparing the prior probability with vs without the factor yields the prior inclusion odds (usually 1, but not always). WebArguments logml. a vector with log-marginal likelihoods. Alternatively, a list with meta-analysis models (fitted via meta_random or meta_fixed).. include. integer vector which models to include in inclusion Bayes factor/posterior probability.
BF10 and BFinclusion in Bayesian ANOVA — Forum
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Assessing the Gender Gap in Access to Digital Financial
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