- Operating System: Linux
- brms Version: version 2.8.0

The help page provides an example of hypothesis for all levels of a grouping factor:

```
prior <- c(set_prior("normal(0,2)", class = "b"),
set_prior("student_t(10,0,1)", class = "sigma"),
set_prior("student_t(10,0,1)", class = "sd"))
## fit a linear mixed effects models
fit <- brm(time ~ age + sex + disease + (1 + age|patient),
data = kidney, family = lognormal(),
prior = prior, sample_prior = TRUE,
control = list(adapt_delta = 0.95))
## compute hypotheses for all levels of a grouping factor
hypothesis(fit, "age = 0", scope = "coef", group = "patient")
Hypothesis Tests for class :
Group Hypothesis Estimate Est.Error CI.Lower CI.Upper Evid.Ratio Post.Prob Star
1 1 (age) = 0 -0.01 0.02 -0.04 0.03 NA NA
2 2 (age) = 0 -0.01 0.02 -0.05 0.03 NA NA
3 3 (age) = 0 -0.01 0.02 -0.04 0.03 NA NA
4 4 (age) = 0 0.00 0.02 -0.04 0.03 NA NA
5 5 (age) = 0 -0.01 0.02 -0.04 0.03 NA NA
6 6 (age) = 0 -0.01 0.02 -0.04 0.03 NA NA
7 7 (age) = 0 -0.01 0.02 -0.04 0.03 NA NA
etc
```

I have a similar model and would like to be able to get evidence ratios for each level of the grouping factor. What am I missing?

Thanks