- Operating System: Windows 10
- brms Version: 2.8.0

I do not understand how to interpret random slopes from the output of `brms`

,

despite reading the informative vignettes and the 2 following papers:

brms: An R Package for Bayesian Multilevel Models

using Stan

Advanced Bayesian Multilevel Modeling

with the R Package brms

Among others, I read this post on the output from `lmer`

and I understood something about random slope interpretation.

However instead of `Variance`

in brms I have `Estimate`

, as for fixed factor!!.

This page also helped me a bit.

In the following example the variable “experience.Mom” has a positive estimate at the group level (random slope) which, if I understand correctly is always the case (why??), and a negative effect at the population level. (intervals are over the 0 so no clear effect anyhow).

What does my random slope `Estimate`

means? Why don’t I have a value for each level of my intercept? How does it influence my outcome variable (Y)?

I hope I explained myself, if what I ask is unclear please tell what to improve.

```
#Group level (random)
Estimate Est.Error l-95% CI u-95% CI Eff.Sample
sd(Intercept) 0.08 0.06 0.00 0.23 4323
sd(experience_Mom.z) 0.09 0.06 0.00 0.24 4831
cor(Intercept,experience_Mom.z) 0.00 0.57 -0.94 0.95 7528
# Population level (fixed)
Estimate Est.Error l-95% CI
experience_Mom.z -0.02 0.09 -0.20
```

Thank you for any explanation.