Hi all,

I’m using brms to fit animal models estimating heritability and genetic correlations of different traits in a wild mouse species. It’s my first foray into both animal models and Bayesian modeling, so my question is extremely simple, but one I need to ask to make sure I’m understanding how to interpret my results: Can I directly interpret the ‘cor’ parameter from multivariate models as the genetic correlation between two traits?

For models fitted using MCMCglmm, one must calculate genetic correlations from covariances; thus there is post-processing of results. There isn’t a way to do this in brms, but the output results from multivariate models do provide a “cor” term between the intercepts of the two traits. This topic was mentioned, and responded to, in a post from a few years ago, but I’m not 100% sure I’m interpreting this correctly https://groups.google.com/forum/#!msg/brms-users/Edc_dA7uWxM/JebX7Xh6AQAJ. However, after reading that and then reading Paul’s recent tutorial on multivariate modeling https://cran.r-project.org/web/packages/brms/vignettes/brms_multivariate.html, I believe I can interpret this term as I have described above–but again, I definitely want to make sure I’ve well understood this.

For example, in Paul’s vignette, tarsus and back are estimated to have a cor of -0.53:

```
Group-Level Effects:
~dam (Number of levels: 106)
Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
sd(tarsus_Intercept) 0.48 0.05 0.40 0.58 1.00 1011
sd(back_Intercept) 0.25 0.08 0.10 0.40 1.01 301
cor(tarsus_Intercept,back_Intercept) -0.53 0.22 -0.94 -0.09 1.01 457
Tail_ESS
sd(tarsus_Intercept) 1276
sd(back_Intercept) 564
cor(tarsus_Intercept,back_Intercept) 405
```

Does this mean that the genetic correlation is = -0.53 (i.e. no further calculations are necessary, unlike in MCMCglmm)?

Much thanks in advance,

Tracy