tests/testthat/test-LORgee.R

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

skip_if_not_installed("multgee")

data(arthritis, package = "multgee")
m1 <- multgee::ordLORgee(
  y ~ factor(time) + factor(trt) + factor(baseline),
  data = arthritis,
  id = id,
  LORstr = "uniform",
  repeated = time
)

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

test_that("find_predictors", {
  expect_identical(find_predictors(m1), list(conditional = c("time", "trt", "baseline")))
  expect_identical(
    find_predictors(m1, flatten = TRUE),
    c("time", "trt", "baseline")
  )
  expect_identical(find_predictors(m1, effects = "random"), list(random = "id"))
  expect_identical(
    find_predictors(m1, effects = "all", flatten = TRUE),
    c("time", "trt", "baseline", "id")
  )
})

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

test_that("get_response", {
  expect_equal(get_response(m1), na.omit(arthritis)$y, ignore_attr = TRUE)
})

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

test_that("get_random", {
  expect_equal(get_random(m1), arthritis[!is.na(arthritis$y), "id", drop = FALSE], ignore_attr = TRUE)
})

test_that("get_predictors", {
  expect_equal(
    get_predictors(m1),
    na.omit(arthritis)[, c("time", "trt", "baseline"), drop = FALSE],
    ignore_attr = TRUE
  )
})

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

test_that("get_data", {
  expect_identical(nrow(get_data(m1)), 888L)
  expect_identical(
    colnames(get_data(m1)),
    c("y", "time", "trt", "baseline", "id")
  )
})

test_that("find_formula", {
  expect_length(find_formula(m1), 2)
  expect_equal(
    find_formula(m1),
    list(
      conditional = as.formula("y ~ factor(time) + factor(trt) + factor(baseline)"),
      random = as.formula("~id")
    ),
    ignore_attr = TRUE
  )
})

test_that("find_terms", {
  expect_length(find_terms(m1), 3)
  expect_identical(
    find_terms(m1),
    list(
      response = "y",
      conditional = c("factor(time)", "factor(trt)", "factor(baseline)"),
      random = "id"
    )
  )
})

test_that("find_variables", {
  expect_identical(
    find_variables(m1),
    list(
      response = "y",
      conditional = c("time", "trt", "baseline"),
      random = "id"
    )
  )
  expect_identical(
    find_variables(m1, flatten = TRUE),
    c("y", "time", "trt", "baseline", "id")
  )
})

test_that("n_obs", {
  expect_identical(n_obs(m1), 888L)
})

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

test_that("find_parameters", {
  expect_identical(
    find_parameters(m1),
    list(
      conditional = c(
        "beta10",
        "beta20",
        "beta30",
        "beta40",
        "factor(time)3",
        "factor(time)5",
        "factor(trt)2",
        "factor(baseline)2",
        "factor(baseline)3",
        "factor(baseline)4",
        "factor(baseline)5"
      )
    )
  )
  expect_identical(nrow(get_parameters(m1)), 11L)
  expect_identical(
    get_parameters(m1)$Parameter,
    c(
      "beta10",
      "beta20",
      "beta30",
      "beta40",
      "factor(time)3",
      "factor(time)5",
      "factor(trt)2",
      "factor(baseline)2",
      "factor(baseline)3",
      "factor(baseline)4",
      "factor(baseline)5"
    )
  )
})

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

test_that("find_algorithm", {
  expect_identical(find_algorithm(m1), list(algorithm = "Fisher's scoring ML"))
})

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