Inconsistent results between regressionBF and lmBF
Hello! I am computing Bayes Factors in R and have noticed that when I use the regressionBF function in order to compare all additive models (i.e. y ~ .), the regressionBF function does not provide me with the same Bayes Factor for a given model as using the lmBF function. The regressionBF function consistently produces higher BF than the lmBF function. I am just running simple linear regressions, no interactions or categorical variables. Moreover, the top ("best") model using regressionBF actually has a lower Bayes Factor compared to the second-best or third-best models when using the lmBF function. Why is this inconsistent and which method is most reliable?
I'd greatly appreciate any input - thank you very much!