diff --git a/R/rescale_weights.R b/R/rescale_weights.R
index 1f528c77d..ec0c75616 100644
--- a/R/rescale_weights.R
+++ b/R/rescale_weights.R
@@ -60,30 +60,32 @@
 #'   - Asparouhov T. (2006). General Multi-Level Modeling with Sampling
 #'   Weights. Communications in Statistics - Theory and Methods 35: 439-460
 #'
-#' @examplesIf insight::check_if_installed("lme4", quietly = TRUE)
-#' data(nhanes_sample)
-#' head(rescale_weights(nhanes_sample, "SDMVSTRA", "WTINT2YR"))
+#' @examples
+#' if (require("lme4")) {
+#'   data(nhanes_sample)
+#'   head(rescale_weights(nhanes_sample, "SDMVSTRA", "WTINT2YR"))
 #'
-#' # also works with multiple group-variables
-#' head(rescale_weights(nhanes_sample, c("SDMVSTRA", "SDMVPSU"), "WTINT2YR"))
+#'   # also works with multiple group-variables
+#'   head(rescale_weights(nhanes_sample, c("SDMVSTRA", "SDMVPSU"), "WTINT2YR"))
 #'
-#' # or nested structures.
-#' x <- rescale_weights(
-#'   data = nhanes_sample,
-#'   by = c("SDMVSTRA", "SDMVPSU"),
-#'   probability_weights = "WTINT2YR",
-#'   nest = TRUE
-#' )
-#' head(x)
+#'   # or nested structures.
+#'   x <- rescale_weights(
+#'     data = nhanes_sample,
+#'     by = c("SDMVSTRA", "SDMVPSU"),
+#'     probability_weights = "WTINT2YR",
+#'     nest = TRUE
+#'   )
+#'   head(x)
 #'
-#' nhanes_sample <- rescale_weights(nhanes_sample, "SDMVSTRA", "WTINT2YR")
+#'   nhanes_sample <- rescale_weights(nhanes_sample, "SDMVSTRA", "WTINT2YR")
 #'
-#' lme4::glmer(
-#'   total ~ factor(RIAGENDR) * (log(age) + factor(RIDRETH1)) + (1 | SDMVPSU),
-#'   family = poisson(),
-#'   data = nhanes_sample,
-#'   weights = pweights_a
-#' )
+#'   glmer(
+#'     total ~ factor(RIAGENDR) * (log(age) + factor(RIDRETH1)) + (1 | SDMVPSU),
+#'     family = poisson(),
+#'     data = nhanes_sample,
+#'     weights = pweights_a
+#'   )
+#' }
 #' @export
 rescale_weights <- function(data, by, probability_weights, nest = FALSE) {
   if (inherits(by, "formula")) {
diff --git a/man/rescale_weights.Rd b/man/rescale_weights.Rd
index d2eddc894..d9651decb 100644
--- a/man/rescale_weights.Rd
+++ b/man/rescale_weights.Rd
@@ -63,31 +63,31 @@ design, or group and PSU as varying intercepts), depending on the survey
 design that should be mimicked.
 }
 \examples{
-\dontshow{if (insight::check_if_installed("lme4", quietly = TRUE)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
-data(nhanes_sample)
-head(rescale_weights(nhanes_sample, "SDMVSTRA", "WTINT2YR"))
+if (require("lme4")) {
+  data(nhanes_sample)
+  head(rescale_weights(nhanes_sample, "SDMVSTRA", "WTINT2YR"))
 
-# also works with multiple group-variables
-head(rescale_weights(nhanes_sample, c("SDMVSTRA", "SDMVPSU"), "WTINT2YR"))
+  # also works with multiple group-variables
+  head(rescale_weights(nhanes_sample, c("SDMVSTRA", "SDMVPSU"), "WTINT2YR"))
 
-# or nested structures.
-x <- rescale_weights(
-  data = nhanes_sample,
-  by = c("SDMVSTRA", "SDMVPSU"),
-  probability_weights = "WTINT2YR",
-  nest = TRUE
-)
-head(x)
+  # or nested structures.
+  x <- rescale_weights(
+    data = nhanes_sample,
+    by = c("SDMVSTRA", "SDMVPSU"),
+    probability_weights = "WTINT2YR",
+    nest = TRUE
+  )
+  head(x)
 
-nhanes_sample <- rescale_weights(nhanes_sample, "SDMVSTRA", "WTINT2YR")
+  nhanes_sample <- rescale_weights(nhanes_sample, "SDMVSTRA", "WTINT2YR")
 
-lme4::glmer(
-  total ~ factor(RIAGENDR) * (log(age) + factor(RIDRETH1)) + (1 | SDMVPSU),
-  family = poisson(),
-  data = nhanes_sample,
-  weights = pweights_a
-)
-\dontshow{\}) # examplesIf}
+  glmer(
+    total ~ factor(RIAGENDR) * (log(age) + factor(RIDRETH1)) + (1 | SDMVPSU),
+    family = poisson(),
+    data = nhanes_sample,
+    weights = pweights_a
+  )
+}
 }
 \references{
 \itemize{