diff --git a/R/check_heterogeneity_bias.R b/R/check_heterogeneity_bias.R
index b87aa9962..d9bb337f9 100644
--- a/R/check_heterogeneity_bias.R
+++ b/R/check_heterogeneity_bias.R
@@ -31,9 +31,9 @@ check_heterogeneity_bias <- function(x, select = NULL, group = NULL) {
   if (insight::is_model(x)) {
     group <- insight::find_random(x, split_nested = TRUE, flatten = TRUE)
     if (is.null(group)) {
-      insight::format_error("Model is no mixed model. Please provide a mixed model, or a data frame and arguments `select` and `group`.")
+      insight::format_error("Model is no mixed model. Please provide a mixed model, or a data frame and arguments `select` and `group`.") # nolint
     }
-    data <- insight::get_data(x, source = "mf", verbose = FALSE)
+    my_data <- insight::get_data(x, source = "mf", verbose = FALSE)
     select <- insight::find_predictors(x, effects = "fixed", component = "conditional", flatten = TRUE)
   } else {
     if (inherits(select, "formula")) {
@@ -42,15 +42,15 @@ check_heterogeneity_bias <- function(x, select = NULL, group = NULL) {
     if (inherits(group, "formula")) {
       group <- all.vars(group)
     }
-    data <- x
+    my_data <- x
   }
 
-  unique_groups <- .n_unique(data[[group]])
+  unique_groups <- .n_unique(my_data[[group]])
   combinations <- expand.grid(select, group)
 
   result <- Map(function(predictor, id) {
     # demean predictor
-    d <- datawizard::demean(data, select = predictor, group = id, verbose = FALSE)
+    d <- datawizard::demean(my_data, select = predictor, group = id, verbose = FALSE)
 
     # get new names
     within_name <- paste0(predictor, "_within")
diff --git a/tests/testthat/test-check_outliers.R b/tests/testthat/test-check_outliers.R
index ec9bb7ffc..02c6804a5 100644
--- a/tests/testthat/test-check_outliers.R
+++ b/tests/testthat/test-check_outliers.R
@@ -87,12 +87,17 @@ test_that("mcd which", {
   # (not clear why method mcd needs a seed)
   set.seed(42)
   expect_identical(
-    tail(which(check_outliers(mtcars[1:4], method = "mcd", threshold = 45))),
+    tail(which(check_outliers(mtcars[1:4], method = "mcd", threshold = 45, verbose = FALSE))),
     31L
   )
-  out <- check_outliers(mtcars, method = "mcd")
+  expect_warning(
+    {
+      out <- check_outliers(mtcars, method = "mcd")
+    },
+    regex = "The sample size is too small"
+  )
   expect_identical(sum(out), 8L)
-  out <- check_outliers(mtcars, method = "mcd", percentage_central = 0.5)
+  out <- check_outliers(mtcars, method = "mcd", percentage_central = 0.5, verbose = FALSE)
   expect_identical(sum(out), 15L)
 })
 
@@ -228,7 +233,8 @@ test_that("multiple methods with ID", {
       mahalanobis = 20, mahalanobis_robust = 25, mcd = 25,
       optics = 14, lof = 0.005
     ),
-    ID = "car"
+    ID = "car",
+    verbose = FALSE
   ))
   expect_identical(
     x$outlier_var$zscore$mpg$car,