docs, test

R/check_residuals.R

@@ -19,7 +19,8 @@
 #'
 #' @inheritSection simulate_residuals Tests based on simulated residuals
 #'
-#' @seealso [`simulate_residuals()`] and [`check_predictions()`].
+#' @seealso [`simulate_residuals()`], [`check_zeroinflation()`],
+#' [`check_overdispersion()`] and [`check_predictions()`].
 #'
 #' @return The p-value of the test statistics.
 #'

R/simulate_residuals.R

@@ -20,7 +20,8 @@
 #' [`check_residuals()`]. The returned object is of class `DHARMa` and
 #' `performance_simres`.
 #'
-#' @seealso [`check_residuals()`] and [`check_predictions()`].
+#' @seealso [`check_residuals()`], [`check_zeroinflation()`],
+#' [`check_overdispersion()`] and [`check_predictions()`].
 #'
 #' @details This function is a small wrapper around [`DHARMa::simulateResiduals()`].
 #' It basically only sets `plot = FALSE` and adds an additional class attribute
@@ -88,9 +89,10 @@ print.performance_simres <- function(x, ...) {
   # DHARMa's method.
   msg <- paste0(
     "Simulated residuals from a model of class `", class(x$fittedModel)[1],
-    "` based on ", x$nSim, " simulations. Use `check_residuals()` to check ",
-    "uniformity of residuals. It is recommended to refer to `?DHARMa::simulateResiudals`",
-    " and `vignette(\"DHARMa\")` for more information about different settings",
+    "` based on ", x$nSim, " simulations. Use `check_residuals()` to check",
+    " uniformity of residuals or `residuals()` to extract simulated residuals.",
+    " It is recommended to refer to `?DHARMa::simulateResiudals` and",
+    " `vignette(\"DHARMa\")` for more information about different settings",
     " in particular situations or for particular models.\n"
   )
   cat(insight::format_message(msg))

tests/testthat/test-check_residuals.R

@@ -1,10 +1,22 @@
-test_that("check_singularity, lme4", {
+test_that("check_residuals", {
   skip_on_cran()
   skip_if_not_installed("DHARMa")
   set.seed(123)
   dat <- DHARMa::createData(sampleSize = 100, overdispersion = 0.5, family = poisson())
   m <- glm(observedResponse ~ Environment1, family = poisson(), data = dat)
   res <- simulate_residuals(m)
+  expect_identical(
+    capture.output(print(res)),
+    c(
+      "Simulated residuals from a model of class `glm` based on 250",
+      "  simulations. Use `check_residuals()` to check uniformity of residuals or",
+      "  `residuals()` to extract simulated residuals. It is recommended to refer",
+      "  to `?DHARMa::simulateResiudals` and `vignette(\"DHARMa\")` for more",
+      "  information about different settings in particular situations or for",
+      "  particular models."
+    )
+  )
+
   out <- check_residuals(res)
   expect_equal(out, 0.01884602, ignore_attr = TRUE, tolerance = 1e-4)
   expect_identical(