Hi All,
I’m fitting reactiontime (RTs) with exGaussian using brms and would appriciate your help on two basic issues:

Estimates: What I need is to examine effects on the shape of the RT distributions (i.e., mu an tau parameter in the exGaus) in natural scale of second or milliseconds. Yet, since brms is using a ‘log’ link by default its a bit tricky to convert interaction effects, etc and I think this might be a place where students will make code errors. What is the cost of sampling using an ‘identity’ link? Is there a reason we should avoid using ‘identity’ link by default?

Priors: The default priors for the intercept in brms are very specific (and with large values). Any idea where this came from and way? Is the numbers trying to reflect milliseconds? I want to set the prior myself  but I’m sure there is a good reason for these numbers  I just couldn’t figure out what.
Thank you all!
Nitzan
model<brm(
brmsformula(
rt ~ 1,
sigma ~ 1,
beta ~ 1
),
data = df,
warmup = 1,
iter = 2,
cores =1,
chains=1,
backend='cmdstan',
family = exgaussian(link = "identity",
link_sigma = "log",
link_beta = "log"))
)
prior_summary(model)
prior class coef group resp dpar nlpar lb ub source
student_t(3, 523.1, 125.1) Intercept default
normal(1.7, 1.3) Intercept beta default
student_t(3, 0, 2.5) Intercept sigma default