Post hoc and effect size

Hi everyone,

I’m an ecologist and after a while I was able to fit a good hierarquical model with brms.

I’ve seen several ways to do post hoc analysis with a brms fit. I used the emmeans package to do comparisons, which gave me reasonable results. However, I don’t feel confident enough to use it because I don’t know if this method is appropriate for Bayesian posterior.
I thought about using Cohen’s d, but I also don’t know if that is the best approach since I have so many groups (5). It would be a shame to use the wrong post hoc method for a really good and robust Bayesian fit.

Ps: I need to use something similar to effect size, which is more common in ecology.

Any thoughts on that?

Can you share more about your model and what inference you want to make with it?

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I have 5 treatments (4 are with nutrient addition and one is the control area with nothing) where I collected plant traits. The model is:
trait ~ treatment * species + (1|site)

Basically, I want to know if the nutrient addition treatments differs from the control. I don’t need to compare treatments between them, only they with the control area.

Here I have the mean and upper and lower limits form the conditional effects

Here is the comparisons made with the emmeans package.

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