Operating System: Mac OS 10.14

brms Version: 2.10.5

Dear brms and Bayesian modeller community,

I have a partly general partly brms modelling-specific question. Please excuse this as an expression of my state of confusion.

My data is resulting from a cross-sectional (quasi) observational study without intervention. I would like to analyse the association between three variables of interest (physiological and behavioural) in the presence of a fourth design variable:

IV, DV, and M, my potential moderator, are all continuous and best fit with something like exgaussian or skew_normal distribution.

The fourth variable is a binary grouping variable, which reflects a design variable; I recruited old and young participants. The grouping variable, i.e., age, is obviously influencing all other parameters.

So my general question would be: Does it at all make sense to include the two groups into one model?

Having read into the benefits and pitfals of mediation analysis and excluding any attempt to claim causality, I still think mediation might be a legit way to go to get more insight into my data. - Although I am happy to be convinced otherwise. -

So, letâs say mediation is the way to go, and I should combine both groups into one model, would it be best to add factor age group (or maybe age as continuous?) into the model just as an additional factor (or covariate, respectively), like

f1 <- bf(M ~ IV + group , family = âexgaussianâ) # mediator model

f2 <- bf(DV ~ M + group + IV, family = âexgaussianâ) # outcome model

m_ccL <- brm(f1 + f2 + set_rescor(FALSE), data = ebg.df, cores = 4)

or would it make more sense to include an interaction with the grouping variable:

f1 <- bf(M ~ IV * group , family = âexgaussianâ)

f2 <- bf(DV ~ M * group + IV * group, family = âexgaussianâ)

And this is where I am obviously ending in complete confusion because I am wondering whether I need to have this interaction with both the mediator and the DV? To make things worse (or really interesting), running the models for the groups separately shows a diverging effect of the moderator.

And hint to come to a solution in this matter would be very much appreciated.

kirstin