tests/testthat/test-clmm.R

In insight: Easy Access to Model Information for Various Model Objects

skip_if_not_installed("lme4")
skip_if_not_installed("ordinal")

data(wine, package = "ordinal")
data(soup, package = "ordinal")

m1 <- ordinal::clmm(rating ~ temp + contact + (1 | judge), data = wine)
m2 <- ordinal::clmm(SURENESS ~ PROD + (1 | RESP) + (1 | RESP:PROD),
  data = soup,
  link = "probit",
  threshold = "equidistant"
)

test_that("model_info", {
  expect_true(model_info(m1)$is_ordinal)
  expect_true(model_info(m2)$is_ordinal)
  expect_true(model_info(m1)$is_logit)
  expect_true(model_info(m2)$is_probit)
  expect_false(model_info(m1)$is_multinomial)
  expect_false(model_info(m1)$is_linear)
})

test_that("find_predictors", {
  expect_identical(find_predictors(m1), list(conditional = c("temp", "contact")))
  expect_identical(
    find_predictors(m1, effects = "all"),
    list(
      conditional = c("temp", "contact"),
      random = "judge"
    )
  )
  expect_identical(
    find_predictors(m1, effects = "all", flatten = TRUE),
    c("temp", "contact", "judge")
  )
  expect_identical(find_predictors(m2), list(conditional = "PROD"))
  expect_identical(
    find_predictors(m2, effects = "all"),
    list(
      conditional = "PROD",
      random = c("RESP", "PROD")
    )
  )
  expect_identical(
    find_predictors(m2, effects = "all", flatten = TRUE),
    c("PROD", "RESP")
  )
})

test_that("find_random", {
  expect_identical(find_random(m1), list(random = "judge"))
  expect_identical(find_random(m2), list(random = c("RESP", "RESP:PROD")))
  expect_identical(find_random(m2, split_nested = TRUE), list(random = c("RESP", "PROD")))
})

test_that("get_random", {
  expect_equal(get_random(m1), wine[, "judge", drop = FALSE], ignore_attr = TRUE)
  expect_equal(get_random(m2), soup[, c("RESP", "PROD"), drop = FALSE], ignore_attr = TRUE)
})

test_that("find_response", {
  expect_identical(find_response(m1), "rating")
  expect_identical(find_response(m2), "SURENESS")
})

test_that("get_response", {
  expect_equal(get_response(m1), wine$rating, ignore_attr = TRUE)
  expect_equal(get_response(m2), soup$SURENESS, ignore_attr = TRUE)
})

test_that("get_predictors", {
  expect_identical(colnames(get_predictors(m1)), c("temp", "contact"))
  expect_identical(colnames(get_predictors(m2)), "PROD")
})

test_that("link_inverse", {
  expect_equal(link_inverse(m1)(0.2), plogis(0.2), tolerance = 1e-5)
  expect_equal(link_inverse(m2)(0.2), pnorm(0.2), tolerance = 1e-5)
})

test_that("get_data", {
  expect_equal(nrow(get_data(m1)), 72)
  expect_identical(
    colnames(get_data(m1)),
    c("rating", "temp", "contact", "judge")
  )
  expect_equal(nrow(get_data(m2)), 1847)
  expect_identical(colnames(get_data(m2)), c("SURENESS", "PROD", "RESP"))
})

test_that("find_formula", {
  expect_length(find_formula(m1), 2)
  expect_equal(
    find_formula(m1),
    list(
      conditional = as.formula("rating ~ temp + contact"),
      random = as.formula("~1 | judge")
    ),
    ignore_attr = TRUE
  )
  expect_length(find_formula(m2), 2)
  expect_equal(
    find_formula(m2),
    list(
      conditional = as.formula("SURENESS ~ PROD"),
      random = list(as.formula("~1 | RESP"), as.formula("~1 | RESP:PROD"))
    ),
    ignore_attr = TRUE
  )
})

test_that("find_terms", {
  expect_identical(
    find_terms(m1),
    list(
      response = "rating",
      conditional = c("temp", "contact"),
      random = "judge"
    )
  )
  expect_identical(
    find_terms(m1, flatten = TRUE),
    c("rating", "temp", "contact", "judge")
  )
  expect_identical(
    find_terms(m2),
    list(
      response = "SURENESS",
      conditional = "PROD",
      random = c("RESP", "PROD")
    )
  )
  expect_identical(
    find_terms(m2, flatten = TRUE),
    c("SURENESS", "PROD", "RESP")
  )
})

test_that("n_obs", {
  expect_equal(n_obs(m1), 72)
  expect_equal(n_obs(m2), 1847)
})

test_that("linkfun", {
  expect_false(is.null(link_function(m1)))
  expect_false(is.null(link_function(m2)))
})

test_that("find_parameters", {
  expect_identical(
    find_parameters(m1),
    list(
      conditional = c("1|2", "2|3", "3|4", "4|5", "tempwarm", "contactyes")
    )
  )
  expect_identical(
    find_parameters(m2),
    list(conditional = c("threshold.1", "spacing", "PRODTest"))
  )
})

test_that("is_multivariate", {
  expect_false(is_multivariate(m1))
  expect_false(is_multivariate(m2))
})

if (getRversion() > "3.6.3") {
  skip_on_cran() ## FIXME: check on win-devel
  test_that("get_variance", {
    expect_equal(
      get_variance(m1),
      list(
        var.fixed = 3.23207765938872,
        var.random = 1.27946088209319,
        var.residual = 3.28986813369645,
        var.distribution = 3.28986813369645,
        var.dispersion = 0,
        var.intercept = c(judge = 1.27946088209319)
      ),
      tolerance = 1e-4
    )
    expect_equal(
      get_variance(m2),
      list(
        var.fixed = 0.132313576370902,
        var.random = 0.193186321588604,
        var.residual = 1,
        var.distribution = 1,
        var.dispersion = 0,
        var.intercept = c(`RESP:PROD` = 0.148265480396059, RESP = 0.0449208411925493)
      ),
      tolerance = 1e-4
    )
  })
}

test_that("find_statistic", {
  expect_identical(find_statistic(m1), "z-statistic")
  expect_identical(find_statistic(m2), "z-statistic")
})