If you run an identical Generalised Additive Mixed Model with the `mgcv`

vs. `brms`

package in `R`

, the summary tables for the factor smooth terms (e.g., `te(..., bs='fs', ...)`

are different. For example, the generic model could be:

```
gam1 <-gam(DV ~
ExpTrialOrder +
FactorA +
s(CovariateM) +
s(ExpTrialOrder, Participant, bs='fs', m=1),
...)
```

```
brms_gam1 <- brm(DV ~
ExpTrialOrder +
FactorA +
s(CovariateM) +
s(ExpTrialOrder, Participant, bs='fs', m=1),
...)
```

For the *traditional* GAMM, the `s(ExpTrialOrder, Participant, bs='fs', m=1)`

part of the table could look like this:

```
Approximate significance of smooth terms:
edf Ref.df F p-value
s(ExpTrialOrder,Participant) 134.282 368.000 59.88 <2e-16
```

while the output from `brms`

could look like this:

```
Smooth Terms:
Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
sds(sExpTrialOrderParticipant_1) 5.91 0.61 4.77 7.13 1.00 2333 4650
sds(sExpTrialOrderParticipant_2) 139.72 15.71 112.74 174.20 1.00 634 1720
```

How should we read the summary table from `brms`

? Are the two components (i.e., `_1`

and `_2`

) smooths for the two components of the `s()`

; that is, **Estimate** == **edf**, for **ExpTrialOrder** and **Participant**, respectively?

- Operating System: macOS
- brms Version: 2.17.0

Thanks!