Hi everyone,
I’m a beginner in brms, so I might be missing something obvious here.
So I’m fitting a number of ordinal probit models on an ordinal variable. One of the independent variables is a categorical variable “condition” with 5 levels: active_arrhTMS, active_rhTMS, baseline, sham_arrhTMS and sham_rhTMS. Logically, I would expect all of these levels to appear in population-level effects. However, active_arrhTMS is missing. Please see the model and the resulting brmsfit object below. Might there be a particular reason for an effect to be discarded when fitting?
model_task_5 <- formula(probe.response ~ zbv * zlog.apen + probeix + block_num + condition + visit + (1|subj/condition))
model_task_5_fit <- brm(model_task_5, data = dataset, family =cumulative("probit"), init=init, iter = 5000, control = list(adapt_delta = 0.99, max_treedepth = 12)) %>%
add_criterion(c("loo"))
Operating System: macOS Monterey Version 12.3.1
brms Version: 2.16.3