add tests

tests/testthat/_snaps/complete_separation.md

@@ -0,0 +1,62 @@
+# print warning about complete separation
+
+    Code
+      print(out)
+    Output
+      Parameter   | Log-Odds |       SE |                95% CI |         z |      p
+      ------------------------------------------------------------------------------
+      (Intercept) |   -66.10 | 1.83e+05 | [-10644.72, 10512.52] | -3.60e-04 | > .999
+      x1          |    15.29 | 27362.84 | [ -3122.69,         ] |  5.59e-04 | > .999
+      x2          |     6.24 | 81543.72 | [-12797.28,         ] |  7.65e-05 | > .999
+    Message
+      
+      Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
+        computed using a Wald z-distribution approximation.
+      
+      The model has a log- or logit-link. Consider using `exponentiate =
+        TRUE` to interpret coefficients as ratios.
+        
+      Note that some coefficients are very large, which may indicate issues
+        with complete separation.
+
+---
+
+    Code
+      print(out)
+    Output
+      Parameter   | Log-Odds |       SE |            95% CI |         z |     p
+      -------------------------------------------------------------------------
+      (Intercept) |   -83.33 | 15505.03 | [       , 816.56] | -5.37e-03 | 0.996
+      gear        |    21.01 |  3876.26 | [-248.93,       ] |  5.42e-03 | 0.996
+    Message
+      
+      Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
+        computed using a Wald z-distribution approximation.
+      
+      The model has a log- or logit-link. Consider using `exponentiate =
+        TRUE` to interpret coefficients as ratios.
+        
+      Note that some coefficients are very large, which may indicate issues
+        with complete separation.
+
+# print warning about quasi complete separation
+
+    Code
+      print(out)
+    Output
+      Parameter   | Log-Odds |    SE |            95% CI |     z |     p
+      ------------------------------------------------------------------
+      (Intercept) |   -56.36 | 21.45 | [-114.76, -25.33] | -2.63 | 0.009
+      qsec        |     3.12 |  1.19 | [   1.40,   6.37] |  2.62 | 0.009
+    Message
+      
+      Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
+        computed using a Wald z-distribution approximation.
+      
+      The model has a log- or logit-link. Consider using `exponentiate =
+        TRUE` to interpret coefficients as ratios.
+        
+      Note that some coefficients are very large, which may indicate issues
+        with (quasi) complete separation. Consider using bias-corrected or
+        penalized regression models.
+

tests/testthat/test-complete_separation.R

@@ -0,0 +1,42 @@
+skip_if(getRversion() < "4.0.0")
+skip_if_not_installed("withr")
+
+withr::with_options(
+  list("parameters_warning_exponentiate" = TRUE),
+  {
+    test_that("print warning about complete separation", {
+      d_sep <- data.frame(
+        y = c(0, 0, 0, 0, 1, 1, 1, 1),
+        x1 = c(1, 2, 3, 3, 5, 6, 10, 11),
+        x2 = c(3, 2, -1, -1, 2, 4, 1, 0)
+      )
+      m_sep <- suppressWarnings(glm(y ~ x1 + x2, data = d_sep, family = binomial))
+      out <- model_parameters(m_sep)
+      expect_snapshot(print(out))
+    })
+  }
+)
+
+withr::with_options(
+  list("parameters_warning_exponentiate" = TRUE),
+  {
+    test_that("print warning about complete separation", {
+      data(mtcars)
+      m_sep2 <- suppressWarnings(glm(am ~ gear, data = mtcars, family = binomial))
+      out <- model_parameters(m_sep2)
+      expect_snapshot(print(out))
+    })
+  }
+)
+
+withr::with_options(
+  list("parameters_warning_exponentiate" = TRUE),
+  {
+    test_that("print warning about quasi complete separation", {
+      data(mtcars)
+      m_sep3 <- suppressWarnings(glm(vs ~ qsec, data = mtcars, family = binomial))
+      out <- model_parameters(m_sep3)
+      expect_snapshot(print(out))
+    })
+  }
+)