tests/testthat/test-makeCorrLoadings.R

In LikertMakeR: Synthesise and Correlate Likert Scale and Rating-Scale Data Based on Summary Statistics

# test-makeCorrLoadings.R

test_that("makeCorrLoadings returns a valid correlation matrix by default", {
  Lambda <- matrix(
    c(
      0.05, 0.20, 0.70,
      0.10, 0.05, 0.80,
      0.05, 0.15, 0.85,
      0.20, 0.85, 0.15,
      0.05, 0.85, 0.10,
      0.10, 0.90, 0.05,
      0.90, 0.15, 0.05,
      0.80, 0.10, 0.10
    ),
    nrow = 8, ncol = 3, byrow = TRUE
  )
  Phi <- matrix(
    c(
      1.0, 0.7, 0.6,
      0.7, 1.0, 0.4,
      0.6, 0.4, 1.0
    ),
    nrow = 3, byrow = TRUE
  )

  R <- makeCorrLoadings(Lambda, Phi)

  # Check dimensions: 8 items -> 8x8 matrix
  expect_true(is.matrix(R))
  expect_equal(nrow(R), 8)
  expect_equal(ncol(R), 8)

  # Diagonal elements should be close to 1
  expect_equal(diag(R), rep(1, 8), tolerance = 1e-6)

  # Correlation matrix should be symmetric
  expect_true(isSymmetric(R))
})



test_that("makeCorrLoadings warns on invalid inputs", {
  # 1) Non-finite loadings
  badLoadings <- matrix(c(NA, Inf, 0.2, 0.1), nrow = 2)

  # 2) Non-positive-definite factorCor (2x2, but second row is repeated, guaranteeing rank deficiency)
  badPhi <- matrix(c(1, 1, 1, 1), nrow = 2)

  expect_warning(
    makeCorrLoadings(badLoadings, factorCor = diag(2)),
    regexp = "Some loadings were non-finite" # or partial text from your warning message
  )

  # Replacing with zeros, now the loadings are effectively c(0, 0, 0.2, 0.1).
  # Next, we also expect a warning from a non-PD factorCor.

  expect_warning(
    makeCorrLoadings(matrix(c(0.2, 0.1, 0.3, 0.4), nrow = 2),
      factorCor = badPhi
    ),
    regexp = "is not positive definite"
  )
})