context("p_significance")

test_that("p_significance", {
  set.seed(333)
  x <- bayestestR::distribution_normal(10000, 1, 1)
  ps <- bayestestR::p_significance(x)
  testthat::expect_equal(as.numeric(ps), 0.816, tolerance = 0.1)
  testthat::expect_equal(nrow(p_significance(data.frame(replicate(4, rnorm(100))))), 4)
  testthat::expect_is(ps, "p_significance")
  testthat::expect_equal(tail(capture.output(print(ps)), 1), "ps [0.10] = 81.60%")
})


if (require("insight")) {
  m <- insight::download_model("stanreg_merMod_5")
  p <- insight::get_parameters(m, effects = "all")

  testthat::expect_equal(
    p_significance(m, effects = "all")$ps[1],
    0.988,
    tolerance = 1e-3
  )
}