fix issues

R/check_model.R

@@ -373,7 +373,7 @@ check_model.model_fit <- function(x,
 
   dat$VIF <- .diag_vif(model, verbose = verbose)
   dat$QQ <- switch(residual_type,
-    simulated = simulate_residuals(model),
+    simulated = simulate_residuals(model, ...),
     .diag_qq(model, model_info = model_info, verbose = verbose)
   )
   dat$REQQ <- .diag_reqq(model, level = 0.95, model_info = model_info, verbose = verbose)
@@ -404,7 +404,7 @@ check_model.model_fit <- function(x,
   dat$VIF <- .diag_vif(model, verbose = verbose)
   dat$QQ <- switch(
     residual_type,
-    simulated = simulate_residuals(model),
+    simulated = simulate_residuals(model, ...),
     .diag_qq(model, model_info = model_info, verbose = verbose)
   )
   dat$HOMOGENEITY <- .diag_homogeneity(model, verbose = verbose)

R/check_overdispersion.R

@@ -6,7 +6,8 @@
 #'
 #' @param x Fitted model of class `merMod`, `glmmTMB`, `glm`, or `glm.nb`
 #'   (package **MASS**), or an object returned by `simulate_residuals()`.
-#' @param ... Currently not used.
+#'
+#' @inheritParams check_zeroinflation
 #'
 #' @return A list with results from the overdispersion test, like chi-squared
 #'   statistics, p-value or dispersion ratio.
@@ -153,6 +154,9 @@ print.check_overdisp <- function(x, digits = 3, ...) {
 
 #' @export
 check_overdispersion.glm <- function(x, verbose = TRUE, ...) {
+  # for warning message
+  model_name <- insight::safe_deparse(substitute(x))
+
   # check if we have poisson
   info <- insight::model_info(x)
   if (!info$is_count && !info$is_binomial) {
@@ -295,16 +299,13 @@ check_overdispersion.glmmTMB <- check_overdispersion.merMod
 
 #' @rdname check_overdispersion
 #' @export
-check_overdispersion.performance_simres <- function(x,
-                                                    tolerance = 0.1,
-                                                    alternative = c("two.sided", "less", "greater"),
-                                                    ...) {
+check_overdispersion.performance_simres <- function(x, alternative = c("two.sided", "less", "greater"), ...) {
   # match arguments
   alternative <- match.arg(alternative)
 
   # statistics function
   variance <- stats::sd(x$simulatedResponse)^2
-  dispersion <- function(i) var(i - x$fittedPredictedResponse) / variance
+  dispersion <- function(i) stats::var(i - x$fittedPredictedResponse) / variance
 
   # compute test results
   result <- .simres_statistics(x, statistic_fun = dispersion, alternative = alternative)

R/simulate_residuals.R

@@ -40,7 +40,9 @@ simulate_residuals <- function(x, iterations = 250, ...) {
   # TODO (low priority): Note that DHARMa::simulateResiduals(x, ...) does its own checks for whether
   # or not the model passed to it is supported, do we want to use this or do our
   # own checks so we can supply our own error message?
-  #
+  if (iterations < 2) {
+    insight::format_error("`iterations` must be at least 2.")
+  }
   # It's important to preserve this object as is, rather than prematurely
   # extracting the residuals from it because the object contains important stuff
   # in it that we'll want to pass onto other functions later, such as passing

inst/WORDLIST

@@ -46,6 +46,7 @@ DOI
 Datenerhebung
 Delacre
 Deskriptivstatistische
+DHARMa
 Distinguishability
 Dom
 Dominicy
@@ -76,6 +77,7 @@ Gazen
 Gelman
 Gnanadesikan
 Guilford
+Hartig
 HDI
 HJ
 Hastie
@@ -124,6 +126,7 @@ Ley
 Leys
 Lillo
 Liu
+Lohse
 Lomax
 MADs
 MSA
@@ -182,6 +185,7 @@ Sensivity
 Shachar
 Shinichi
 Skrondal
+Smyth
 Solomons
 Somers
 Specifity
@@ -279,6 +283,7 @@ metafor
 mfx
 mhurdle
 mis
+misspecification
 mlm
 mlogit
 modelfit
@@ -302,6 +307,7 @@ quartile
 quartiles
 rOpenSci
 recoding
+reimplement
 rempsyc
 reproducibility
 rescaling
@@ -325,6 +331,7 @@ unadjusted
 und
 underfitted
 underfitting
+underdispersion
 visualisation
 winsorization
 winsorize

tests/testthat/test-check_model.R

@@ -64,11 +64,8 @@ test_that("`check_model()` warnings for tweedie", {
   ))
   expect_message(
     expect_message(
-      expect_message(
-        check_model(m, iterations = 1, verbose = TRUE),
-        regex = "Not enough model terms"
-      ),
-      regex = "QQ plot could not"
+      check_model(m, iterations = 2, verbose = TRUE),
+      regex = "Not enough model terms"
     )
   )
 })

tests/testthat/test-check_residuals.R

@@ -11,6 +11,8 @@ test_that("check_singularity, lme4", {
     capture.output(print(out)),
     "Warning: Non-uniformity of simulated residuals detected (p = 0.019)."
   )
+  expect_error(simulate_residuals(m, iterations = 1), "`iterations` must be")
+
   skip_if_not_installed("MASS")
   set.seed(3)
   mu <- rpois(500, lambda = 3)