context("SEMinR correctly estimates PLS-MGA\n")

test_that("Seminr estimates the correct PLS-MGA p-values", {
  # Test cases
  mobi <- mobi

  #seminr syntax for creating measurement model
  mobi_mm <- constructs(
    composite("Image",        multi_items("IMAG", 1:5)),
    composite("Expectation",  multi_items("CUEX", 1:3)),
    composite("Quality",      multi_items("PERQ", 1:7)),
    composite("Value",        multi_items("PERV", 1:2)),
    composite("Satisfaction", multi_items("CUSA", 1:3)),
    composite("Complaints",   single_item("CUSCO")),
    composite("Loyalty",      multi_items("CUSL", 1:3))
  )

  #seminr syntax for creating structural model
  mobi_sm <- relationships(
    paths(from = "Image",        to = c("Expectation", "Satisfaction", "Loyalty")),
    paths(from = "Expectation",  to = c("Quality", "Value", "Satisfaction")),
    paths(from = "Quality",      to = c("Value", "Satisfaction")),
    paths(from = "Value",        to = c("Satisfaction")),
    paths(from = "Satisfaction", to = c("Complaints", "Loyalty")),
    paths(from = "Complaints",   to = "Loyalty")
  )

  mobi_pls <- estimate_pls(data = mobi,
                           measurement_model = mobi_mm,
                           structural_model = mobi_sm,
                           missing = mean_replacement,
                           missing_value = NA)

  set.seed(798234)
  rand_cond <- sample(c(TRUE, FALSE), nrow(mobi), replace = TRUE)
  mobi_mga <- estimate_pls_mga(mobi_pls, rand_cond, nboot=100, cores = 2)

  ## Output originally created using following lines (put in correct fixtures folder)
  # fixture_file <- "tests/fixtures/V_3_6_0/pls-mga-mobi-100.RDS"
  # file.remove(fixture_file)
  # saveRDS(mobi_mga, file = fixture_file)

  # Load controls
  mga_correct <- readRDS(paste(test_folder, "pls-mga-mobi-100.RDS", sep = ""))

  # Testing
  expect_equal(mobi_mga$pls_mga_p, mga_correct$pls_mga_p, tolerance = 0.00001)
})