tests/testthat/test-genNLR.R

In difNLR: DIF and DDF Detection by Non-Linear Regression Models

test_that("genNLR - examples at help page", {
  # skip_on_cran()
  # skip_on_os("linux")

  # seed
  set.seed(123)
  # generating parameters for dichotomous data with DIF, 5 items
  a <- matrix(runif(10, 0.8, 2), ncol = 2)
  b <- matrix(runif(10, -2, 2), ncol = 2)
  c <- matrix(runif(10, 0, 0.25), ncol = 2)
  d <- matrix(runif(10, 0.8, 1), ncol = 2)
  # generating dichotomous data set with 300 observations (150 each group)
  expect_snapshot(genNLR(N = 300, a = a, b = b, c = c, d = d))
  # generating dichotomous data set with 300 observations (150 each group)
  # and different mean and standard deviation for underlying distribution
  expect_snapshot(genNLR(N = 300, a = a, b = b, c = c, d = d, mu = c(1, 0), sigma = c(1, 2)))
  # generating dichotomous data set with 300 observations (250 reference group, 50 focal)
  expect_snapshot(genNLR(N = 300, ratio = 5, a = a, b = b, c = c, d = d))

  # generating parameters for nominal data with DDF, 5 items,
  # each item 3 choices
  a <- matrix(runif(20, 0.8, 2), ncol = 4)
  b <- matrix(runif(20, -2, 2), ncol = 4)
  # generating nominal data set with 300 observations (150 each group)
  expect_snapshot(genNLR(N = 300, itemtype = "nominal", a = a, b = b))
  # generating nominal data set with 300 observations (250 reference group, 50 focal)
  expect_snapshot(genNLR(N = 300, itemtype = "nominal", ratio = 5, a = a, b = b))

  # generating parameters for nominal data with DDF, 5 items,
  # items 1 and 2 have 2 choices, items 3, 4 and 5 have 3 choices
  a <- matrix(runif(20, 0.8, 2), ncol = 4)
  a[1:2, c(2, 4)] <- NA
  b <- matrix(runif(20, -2, 2), ncol = 4)
  b[1:2, c(2, 4)] <- NA
  # generating nominal data set with 300 observations (150 each group)
  expect_snapshot(genNLR(N = 300, itemtype = "nominal", a = a, b = b))
  # generating nominal data set with 300 observations (250 reference group, 50 focal)
  expect_snapshot(genNLR(N = 300, itemtype = "nominal", ratio = 5, a = a, b = b))
})

test_that("genNLR - checking inputs", {
  # skip_on_cran()
  # skip_on_os("linux")

  # seed
  set.seed(123)
  # generating parameters for dichotomous data with DIF, 5 items
  a <- matrix(runif(10, 0.8, 2), ncol = 2)
  b <- matrix(runif(10, -2, 2), ncol = 2)
  c <- matrix(runif(10, 0, 0.25), ncol = 2)
  d <- matrix(runif(10, 0.8, 1), ncol = 2)

  # invalid mu
  expect_error(genNLR(N = 300, a = a, b = b, c = c, d = d, mu = NULL))
  expect_warning(genNLR(N = 300, a = a, b = b, c = c, d = d, mu = c(0, 0, 2)))
  # invalid sigma
  expect_error(genNLR(N = 300, a = a, b = b, c = c, d = d, sigma = NULL))
  expect_error(genNLR(N = 300, a = a, b = b, c = c, d = d, sigma = c(0, -1)))
  expect_warning(genNLR(N = 300, a = a, b = b, c = c, d = d, sigma = c(1, 1, 2)))
  # invalid itemtype
  expect_error(genNLR(N = 300, a = a, b = b, c = c, d = d, itemtype = "xxx"))
  # missing a
  expect_error(genNLR(N = 300, b = b, c = c, d = d))
  # missing b
  expect_error(genNLR(N = 300, a = a, c = c, d = d))

  # invalid dimensions in dich itemtype
  expect_error(genNLR(N = 300, a = a[-1, ], b = b, c = c, d = d))
  expect_error(genNLR(N = 300, a = cbind(a, a), b = b, c = c, d = d))
  expect_error(genNLR(N = 300, a = a, b = cbind(b, b), c = c, d = d))
  expect_error(genNLR(N = 300, a = a, b = b, c = cbind(c, c), d = d))
  expect_error(genNLR(N = 300, a = a, b = b, d = cbind(d, d)))
  # missing values in item parameters in dich itemtype
  atmp <- a
  atmp[1, 1] <- NA
  expect_error(genNLR(N = 300, a = atmp, b = b, c = c, d = d, itemtype = "dich"))

  a <- matrix(runif(20, 0.8, 2), ncol = 4)
  b <- matrix(runif(20, -2, 2), ncol = 4)
  # invalid dimensions for a and b in nominal itemtype
  expect_error(genNLR(N = 300, itemtype = "nominal", a = a[, 1:3], b = b))
  expect_error(genNLR(N = 300, itemtype = "nominal", a = a, b = b[, 1:3]))
  expect_error(genNLR(N = 300, itemtype = "nominal", a = a[, 1:2], b = b))
  expect_error(genNLR(N = 300, itemtype = "nominal", a = a, b = b[-1, ]))
  # missing values in item parameters in dich itemtype
  atmp <- a
  atmp[1, 1] <- NA
  btmp <- b
  btmp[2, 3] <- NA
  expect_error(genNLR(N = 300, a = atmp, b = btmp, itemtype = "nominal"))

  a <- matrix(runif(28 * 5, 0.8, 2), ncol = 28)
  b <- matrix(runif(28 * 5, -2, 2), ncol = 28)
  expect_error(genNLR(N = 300, itemtype = "nominal", a = a, b = b))
})

test_that("genNLR - further examples", {
  # skip_on_cran()
  # skip_on_os("linux")

  # seed
  set.seed(123)
  # generating parameters for dichotomous data with DIF, 5 items
  a <- runif(5, 0.8, 2)
  b <- runif(5, -2, 2)
  c <- runif(5, 0, 0.25)
  d <- runif(5, 0.8, 1)
  # generating dichotomous data set with 300 observations (150 each group)
  set.seed(123)
  expect_snapshot((df1 <- genNLR(N = 300, a = a, b = b, c = c, d = d)))

  a <- matrix(a, ncol = 1)
  b <- matrix(b, ncol = 1)
  c <- matrix(c, ncol = 1)
  d <- matrix(d, ncol = 1)
  set.seed(123)
  expect_snapshot((df2 <- genNLR(N = 300, a = a, b = b, c = c, d = d)))
  expect_equal(df1, df2)
})