Hi all,

I am comparing different models with bayes_factor from the package brms and have some issues for interpretation.

If I compare the same model but one with Gaussian, and one with Student distribution

fit1 <- brm(formula = bf(VARIABLE ~ CONDITION + AGE + (1|ID)), save_all_pars = TRUE,

data = myDataFrame)

fit2 <- brm(formula = bf(VARIABLE ~ CONDITION + AGE + (1|ID)), save_all_pars = TRUE,

data = myDataFrame, **family = student()**)

Or if I compare one linear with one polynomial model

fit1 <- brm(formula = bf(VARIABLE ~ CONDITION + AGE + (1|ID)), save_all_pars = TRUE,

data = myDataFrame)

fit3 <- brm(formula = bf(VARIABLE ~ CONDITION + **poly(AGE,2)** + (1|ID)), save_all_pars = TRUE,

data = myDataFrame)

I get bayes_factor = “0” or “inf” depending on which model I put first. How should I interpret that? Does it mean that R can not compute or that one of the model is extremely better ?

Am I doing something wrong here?

Thank you in advance!

Marie