Hello,
I have the following brm model:
fit ← brm(response ~ 0 + Intercept + contrast + syllable + english.use + syllable : contrast + (1 | subject), data = test, family = bernoulli(“logit”), prior = prior, sample_prior = “yes”, control = list(adapt_delta = 0.95))
prior class coef group resp dpar nlpar lb ub source
(flat) b default
(flat) b contrastp_b (vectorized)
(flat) b contrastp_b:syllableOpen (vectorized)
(flat) b contrastt_d (vectorized)
(flat) b contrastt_d:syllableOpen (vectorized)
(flat) b english.useYes (vectorized)
(flat) b Intercept (vectorized)
(flat) b syllableOpen (vectorized)
student_t(3, 0, 2.5) sd 0 default
student_t(3, 0, 2.5) sd subject 0 (vectorized)
student_t(3, 0, 2.5) sd Intercept subject 0 (vectorized)
I would like to use the hypothesis method to make the following pairwise comparisons:
contrastp_b < contrastt_d (both belonging to the level “open” of the variable syllable)
contrastp_b < contrastt_d (both belonging to the level “closed” of syllable)
contrastp_b (belonging to the level “open” of syllable) < contrast p_b (belonging to level “closed” of syllable)
I look forward to hear your suggestions on the R code.
Many thanks,
George