skip_if_not_installed("aod")

data(dja, package = "aod")
m1 <- suppressWarnings(aod::betabin(cbind(y, n - y) ~ group * trisk, ~village, data = dja))

test_that("model_info", {
  expect_true(model_info(m1)$is_binomial)
  expect_true(model_info(m1)$is_betabinomial)
  expect_true(model_info(m1)$is_mixed)
  expect_false(model_info(m1)$is_linear)
})

test_that("find_predictors", {
  expect_identical(find_predictors(m1), list(conditional = c("group", "trisk")))
  expect_identical(find_predictors(m1, flatten = TRUE), c("group", "trisk"))
  expect_identical(find_predictors(m1, effects = "random"), list(random = "village"))
  expect_identical(
    find_predictors(m1, effects = "all"),
    list(
      conditional = c("group", "trisk"),
      random = "village"
    )
  )
})

test_that("find_random", {
  expect_identical(find_random(m1), list(random = "village"))
})

test_that("get_random", {
  expect_equal(get_random(m1), dja[, "village", drop = FALSE], ignore_attr = TRUE)
})

test_that("get_varcov", {
  expect_message(get_varcov(m1))
  expect_equal(get_varcov(m1, pd_tolerance = NULL), aod::vcov(m1), tolerance = 1e-3)
})

test_that("find_response", {
  expect_identical(find_response(m1), "cbind(y, n - y)")
  expect_identical(find_response(m1, combine = FALSE), c("y", "n"))
})

test_that("get_response", {
  expect_equal(get_response(m1, verbose = FALSE), dja[, c("y", "n")])
})

test_that("get_predictors", {
  expect_equal(colnames(get_predictors(m1)), c("group", "trisk"))
})

test_that("link_inverse", {
  expect_equal(link_inverse(m1)(0.2), plogis(0.2), tolerance = 1e-5)
})

test_that("link_function", {
  expect_equal(link_function(m1)(0.2), qlogis(0.2), tolerance = 1e-5)
})

test_that("get_data", {
  expect_equal(nrow(get_data(m1, verbose = FALSE)), 75)
  expect_equal(colnames(get_data(m1, verbose = FALSE)), c("y", "n", "group", "trisk", "village"))
})

test_that("find_formula", {
  expect_length(find_formula(m1), 2)
  expect_equal(
    find_formula(m1),
    list(
      conditional = as.formula("cbind(y, n - y) ~ group * trisk"),
      random = as.formula("~village")
    ),
    ignore_attr = TRUE
  )
})

test_that("find_variables", {
  expect_equal(
    find_variables(m1),
    list(
      response = c("y", "n"),
      conditional = c("group", "trisk"),
      random = "village"
    )
  )
  expect_equal(find_variables(m1, flatten = TRUE), c("y", "n", "group", "trisk", "village"))
})

test_that("n_obs", {
  expect_equal(n_obs(m1), 75)
})

test_that("find_parameters", {
  expect_equal(
    find_parameters(m1),
    list(
      conditional = c("(Intercept)", "groupTREAT", "trisk", "groupTREAT:trisk"),
      random = c(
        "phi.villageBAK", "phi.villageBAM", "phi.villageBAN",
        "phi.villageBIJ", "phi.villageBOU", "phi.villageBYD", "phi.villageDEM",
        "phi.villageDIA", "phi.villageHAM", "phi.villageLAM", "phi.villageLAY",
        "phi.villageMAF", "phi.villageMAH", "phi.villageMAK", "phi.villageMED",
        "phi.villageNAB", "phi.villageSAG", "phi.villageSAM", "phi.villageSOU"
      )
    )
  )
  expect_equal(nrow(get_parameters(m1)), 4)
  expect_equal(get_parameters(m1)$Parameter, c("(Intercept)", "groupTREAT", "trisk", "groupTREAT:trisk"))
})

test_that("is_multivariate", {
  expect_false(is_multivariate(m1))
})

test_that("find_terms", {
  expect_equal(
    find_terms(m1),
    list(
      response = "cbind(y, n - y)",
      conditional = c("group", "trisk"),
      random = "village"
    )
  )
})

test_that("find_algorithm", {
  expect_equal(find_algorithm(m1), list(algorithm = "ML"))
})

test_that("find_statistic", {
  expect_identical(find_statistic(m1), "z-statistic")
})