Hi there! I’d like to run a simple brms model that assumes a shifted lognormal response distribution. I was hoping to get confirmation that I’m correctly translating my raw (RT) unit expectations into specific, log-scaled priors.

I’m investigating a 2x2 interaction of the form “RT ~ A *B.” A previous paper ran a frequentist model that returns the following coefficient estimates.

```
prev_study_rt_intercept <- .5
prev_study_rt_intercept_sd <- .4
prev_study_rt_cond_A <- .2
prev_study_rt_cond_A_sd <- .15
prev_study_rt_cond_B <- .03
prev_study_rt_cond_B_sd <- .1
prev_study_rt_A_x_B <- -.04
prev_study_rt_A_x_B_sd <- .06
```

If I, too, wanted to run an “RT ~ A * B” model, but doing so on new data, in brms, and using a shifted lognormal distribution, would the following code correctly set my priors in line with the findings from the previous study? I’m particularly unsure about whether I’m setting the priors on the sd’s correctly. I used `abs`

to ensure the sd is positive, but the fact that it’s even needed tells me that I might be off.

```
expected_ndt_shift <- 200
prior_intercept <- log(prev_study_rt_intercept - expected_ndt_shift)
prior_intercept_sd <- abs(log(prev_study_rt_intercept_sd))
prior_cond_A <- log(1 + prev_study_rt_cond_A / prev_study_rt_intercept)
prior_cond_A_sd <- abs(log(1 + prev_study_rt_cond_A_sd / prev_study_rt_intercept))
prior_cond_B <- log(1 + prev_study_rt_cond_B / prev_study_rt_intercept)
prior_cond_B_sd <- abs(log(1 + prev_study_rt_cond_B_sd / prev_study_rt_intercept))
prior_cond_A_x_B <- log(1 + prev_study_rt_cond_A_x_B / prev_study_rt_intercept)
prior_cond_A_x_B_sd <- abs(log(1 + prev_study_rt_cond_A_x_B_sd / prev_study_rt_intercept))
my_priors = c(
set_prior(paste0('normal(', prior_intercept, ', ', prior_intercept_sd, ')'), class = 'Intercept'),
set_prior(paste0('normal(', prior_cond_A, ', ', prior_cond_A_sd, ')'), class = 'b', coef = 'A'),
set_prior(paste0('normal(', prior_cond_B, ', ', prior_cond_B_sd, ')'), class = 'b', coef = 'B'),
set_prior(paste0('normal(', prior_cond_A_x_B, ', ', prior_cond_A_x_B_sd, ')'), class = 'b', coef = 'A_x_B'),
)
brm(RT ~ A*B, df, shifted_lognormal(), my_priors)
```

Thanks in advance!