Hello,

I have compared two models with the same priors using the Bayes factor in brms.

```
# Settings for BRMS
niter=20000
nchains=4
adaptdeltas=0.9
h4<- brm(formula= GC_InabilStop ~ b_PrevSearch + Compulsivity+Apathy+DeprAnx+SocialAnx+Age+Gender+mo(EducationLevel),
data=df.h4,save_all_pars = TRUE, family='gaussian',iter=niter,chains=nchains,cores=nchains,control=list(adapt_delta=adaptdeltas))
```

while the other model is reduced removing b_PrevSearch which is the predictor of interest for the experiment.

```
# Settings for BRMS
niter=20000
nchains=4
adaptdeltas=0.9
h4.null<- brm(formula= GC_InabilStop ~ Compulsivity+Apathy+DeprAnx+SocialAnx+Age+Gender+mo(EducationLevel),
data=df.h4,save_all_pars = TRUE, family='gaussian',iter=niter,chains=nchains,cores=nchains,control=list(adapt_delta=adaptdeltas))
```

The BF is 78 in favour of the model that includes the predictor of interest. However, credible intervals of the predictor of interest include zero.

How do i interpret the results?