if (requiet("MASS")) {
  data(housing, package = "MASS")

  m1 <- polr(Sat ~ Infl + Type + Cont, data = housing, weights = Freq)

  test_that("model_info", {
    expect_true(model_info(m1)$is_ordinal)
    expect_false(model_info(m1)$is_multinomial)
  })

  test_that("find_predictors", {
    expect_identical(find_predictors(m1), list(conditional = c("Infl", "Type", "Cont")))
    expect_identical(
      find_predictors(m1, flatten = TRUE),
      c("Infl", "Type", "Cont")
    )
    expect_null(find_predictors(m1, effects = "random"))
  })

  test_that("find_response", {
    expect_identical(find_response(m1), "Sat")
  })

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

  test_that("get_data", {
    expect_equal(nrow(get_data(m1)), 72)
    expect_equal(
      colnames(get_data(m1)),
      c("Sat", "Infl", "Type", "Cont", "Freq")
    )
  })

  test_that("get_df", {
    expect_equal(
      get_df(m1, type = "residual"),
      df.residual(m1),
      ignore_attr = TRUE
    )
    expect_equal(
      get_df(m1, type = "normal"),
      Inf,
      ignore_attr = TRUE
    )
    expect_equal(
      get_df(m1, type = "wald"),
      df.residual(m1), # model has t-statistic
      ignore_attr = TRUE
    )
  })

  test_that("find_formula", {
    expect_length(find_formula(m1), 1)
    expect_equal(
      find_formula(m1),
      list(conditional = as.formula("Sat ~ Infl + Type + Cont")),
      ignore_attr = TRUE
    )
  })

  test_that("find_terms", {
    expect_equal(find_terms(m1), list(
      response = "Sat",
      conditional = c("Infl", "Type", "Cont")
    ))
    expect_equal(
      find_terms(m1, flatten = TRUE),
      c("Sat", "Infl", "Type", "Cont")
    )
  })

  test_that("n_obs", {
    expect_equal(n_obs(m1), 1681)
  })

  test_that("linkfun", {
    expect_false(is.null(link_function(m1)))
  })


  test_that("find_parameters", {
    expect_equal(
      find_parameters(m1),
      list(
        conditional =
          c(
            "Intercept: Low|Medium",
            "Intercept: Medium|High",
            "InflMedium",
            "InflHigh",
            "TypeApartment",
            "TypeAtrium",
            "TypeTerrace",
            "ContHigh"
          )
      )
    )
  })

  test_that("get_parameters", {
    expect_equal(
      get_parameters(m1),
      data.frame(
        Parameter = c(
          "Intercept: Low|Medium",
          "Intercept: Medium|High",
          "InflMedium",
          "InflHigh",
          "TypeApartment",
          "TypeAtrium",
          "TypeTerrace",
          "ContHigh"
        ),
        Estimate = c(
          -0.4961353438375,
          0.690708290379271,
          0.566393738890106,
          1.28881906381232,
          -0.572350146429611,
          -0.366186566153346,
          -1.09101490767244,
          0.360284149947385
        ),
        stringsAsFactors = FALSE,
        row.names = NULL
      )
    )
  })

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

  test_that("get_predicted", {
    p1 <- get_predicted(m1, predict = "expectation")
    p2 <- get_predicted(m1, predict = "classification")
    p3 <- get_predicted(m1, predict = NULL, type = "probs")
    p4 <- get_predicted(m1, predict = NULL, type = "class")
    expect_s3_class(p1, "get_predicted")
    expect_s3_class(p2, "get_predicted")
    expect_s3_class(p3, "get_predicted")
    expect_s3_class(p4, "get_predicted")
    expect_equal(p1, p3)
    expect_equal(p2, p4)
    expect_true(inherits(p1, "data.frame"))
    expect_true(inherits(p2, "factor"))
    expect_true(inherits(p3, "data.frame"))
    expect_true(inherits(p4, "factor"))
    expect_true(all(c("Row", "Response", "Predicted") %in% colnames(p1)))
    expect_true(all(c("Row", "Response", "Predicted") %in% colnames(p3)))

    d <- get_datagrid(m1, at = "Type", verbose = FALSE)

    p1 <- get_predicted(m1, predict = "expectation", data = d, verbose = FALSE)

    expect_equal(colnames(p1), c("Row", "Type", "Response", "Predicted"))
    expect_equal(dim(p1), c(12, 4))
  })
}
