R Under development (unstable) (2026-11-02 r90827 ucrt) -- "Unsuffered Consequences"
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> # This script is intentionally outside tests/testthat: R CMD check runs it in a
> # fresh process where BayesTools is installed but not attached.
> 
> make_prior <- function(contrast){
+ 
+   switch(
+     contrast,
+     treatment = BayesTools::prior_factor(
+       "normal", list(0, 1), contrast = "treatment"
+     ),
+     independent = BayesTools::prior_factor(
+       "normal", list(0, 1), contrast = "independent"
+     ),
+     orthonormal = BayesTools::prior_factor(
+       "mnormal", list(0, 1), contrast = "orthonormal"
+     ),
+     meandif = BayesTools::prior_factor(
+       "mnormal", list(0, 1), contrast = "meandif"
+     ),
+     cumulative = BayesTools::prior_ordered(
+       BayesTools::prior("normal", list(0, 1)),
+       contrast = "cumulative"
+     ),
+     cumulative_levels = BayesTools::prior_ordered(
+       BayesTools::prior("normal", list(0, 1)),
+       contrast = "cumulative_levels"
+     )
+   )
+ }
> 
> contrast_names <- c(
+   "treatment",
+   "independent",
+   "orthonormal",
+   "meandif",
+   "cumulative",
+   "cumulative_levels"
+ )
> 
> for(contrast_name in contrast_names){
+   factor_data <- factor(
+     rep(c("a", "b", "c"), 2),
+     levels = c("a", "b", "c"),
+     ordered = grepl("cumulative", contrast_name, fixed = TRUE)
+   )
+   result <- BayesTools::JAGS_formula(
+     formula   = ~ group,
+     parameter = "mu",
+     data      = data.frame(group = factor_data),
+     prior_list = list(
+       intercept = BayesTools::prior("normal", list(0, 1)),
+       group     = make_prior(contrast_name)
+     )
+   )
+ 
+   stopifnot(
+     inherits(result$formula_design, "BayesTools_formula_design"),
+     nrow(result$formula_design$model_matrix) == length(factor_data)
+   )
+ }
> 
> random_data <- data.frame(
+   group = factor(rep(c("a", "b", "c"), 2), levels = c("a", "b", "c")),
+   id    = factor(rep(c("g1", "g2", "g3"), each = 2))
+ )
> random_result <- BayesTools::JAGS_formula(
+   formula   = ~ 1 + diag(0 + group | id),
+   parameter = "mu",
+   data      = random_data,
+   prior_list = list(
+     intercept = BayesTools::prior("normal", list(0, 1))
+   ),
+   prior_random = BayesTools::prior_random(
+     id = BayesTools::random_block(
+       sd = BayesTools::prior("gamma", list(2, 2)),
+       contrasts = c(group = "orthonormal")
+     )
+   )
+ )
> random_term <- random_result$formula_design$random_effects[[1L]]
> random_prediction <- BayesTools:::.bt_random_effect_prediction_data(
+   random_term,
+   data = random_data
+ )
> 
> stopifnot(
+   identical(random_term$contrasts$group, "contr.orthonormal"),
+   identical(random_prediction$model_matrix, random_term$model_matrix)
+ )
> 
> proc.time()
   user  system elapsed 
   1.14    0.28    1.37