test_that("bayesmsm works with no errors", {
  library(MCMCpack)
  library(doParallel)
  library(foreach)
  testdata <- simData(
    n                = 50,
    n_visits         = 2,
    covariate_counts = c(2, 2),
    # inline treatment models
    amodel = list(
      c("(Intercept)" =  0, "L1_1" =  0.5, "L2_1" = -0.5),
      c("(Intercept)" =  0, "L1_2" =  0.5, "L2_2" = -0.5, "A_prev" = 0.3)
    ),
    # inline outcome model
    ymodel = c("(Intercept)" = 0,
               "A1"         = 0.2,
               "A2"         = 0.3,
               "L1_2"       = 0.1,
               "L2_2"       = -0.1),
    y_type       = "continuous",
    right_censor = FALSE,
    seed         = 101
  )
  model <- bayesmsm(ymodel = Y ~ A1 + A2,
                    nvisit = 2,
                    reference = c(rep(0,2)),
                    comparator = c(rep(1,2)),
                    treatment_effect_type = "sq",
                    family = "binomial",
                    data = testdata,
                    wmean = rep(1,50),
                    nboot = 10,
                    optim_method = "BFGS",
                    seed = 890123,
                    parallel = FALSE)

  # Check if 'model' is a list
  expect_true(is.list(model))

  # Check if 'model' has 12 elements
  expect_length(model, 12)

  # Check if 'model' has the correct names
  expected_names <- c('RD_mean', 'RR_mean', 'OR_mean',
                      'RD_sd', 'RR_sd', 'OR_sd',
                      'RD_quantile', 'RR_quantile', 'OR_quantile',
                      'bootdata', 'reference', 'comparator')
  expect_named(model, expected_names)
})