add tests

R/p_significance.R

@@ -67,7 +67,12 @@ p_significance.lm <- function(x, threshold = "default", ci = 0.95, verbose = TRU
     verbose = verbose
   ))
 
-  attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(x))
+  # for plot, we need to have it numeric
+  if (!is.numeric(threshold)) {
+    threshold <- 0.1
+  }
+
+  attr(out, "data") <- posterior
   attr(out, "threshold") <- threshold
   class(out) <- c("p_significance_lm", "p_significance", "see_p_significance", "data.frame")
   out

tests/testthat/_snaps/p_significance.md

@@ -0,0 +1,15 @@
+# p_significance
+
+    Code
+      print(x)
+    Output
+      Practical Significance (threshold: default)
+      
+      Parameter   |         95% CI |         ps
+      -----------------------------------------
+      (Intercept) | [24.44, 48.94] |  ps > .999
+      gear        | [-1.69,  2.41] | ps = 0.663
+      wt          | [-4.77, -1.28] |  ps > .999
+      cyl         | [-2.17,  0.55] | ps = 0.958
+      hp          | [-0.05,  0.01] |  ps < .001
+

tests/testthat/test-p_significance.R

@@ -0,0 +1,19 @@
+skip_if_not_installed("bayestestR")
+
+test_that("p_significance", {
+  data(mtcars)
+  m <- lm(mpg ~ gear + wt + cyl + hp, data = mtcars)
+  set.seed(123)
+  x <- p_significance(m)
+  expect_identical(c(nrow(x), ncol(x)), c(5L, 5L))
+  expect_named(x, c("Parameter", "CI", "CI_low", "CI_high", "ps"))
+  expect_snapshot(print(x))
+
+  set.seed(123)
+  x <- p_significance(m, ci = 0.8)
+  expect_equal(x$ps, c(1, 0.7446, 1, 0.9964, 0), tolerance = 1e-4)
+
+  set.seed(123)
+  x <- p_significance(m, threshold = 0.5)
+  expect_equal(x$ps, c(1, 0.4128, 1, 0.7751, 0), tolerance = 1e-4)
+})