Hello,

I am using brms to run Multilevel models. I am comparing two models, with the same random structure and prior, using bayes_factor, as below

```
prior_rt = c(set_prior("normal(475, 100)", class = "Intercept"),
set_prior("normal(0, 10)", class = "b"),
set_prior("normal(0, 10)", class = "sd"),
set_prior("normal(0, 10)", class = "sigma"))
model1= brm(RT ~ factor1* factor2+ (factor1* factor2| num_part)
, data = data_go_correct_seq
, family = exgaussian(link = "identity")
, warmup = 500
, iter = 3000
, chains = 2
, init = "0"
, cores = 2
, seed = 123
, prior = prior_rt
, save_pars = save_pars(all = TRUE)
)
model2= brm(RT ~ factor2+ (factor1* factor2| num_part)
, data = data_go_correct_seq
, family = exgaussian(link = "identity")
, warmup = 500
, iter = 3000
, chains = 2
, init = "0"
, cores = 2
, seed = 123
, prior = prior_rt
, save_pars = save_pars(all = TRUE)
)
bayes_factor(model1, model2)
# Estimated Bayes factor in favor of model2 over model1: 0.00000
```

The result is 0.000. Is there an error? Because by looking at the summary of the models is clear that model 1 is better than model 2. I am confronting them because I am interested in the effect of factor 1

Thank you,