diff --git a/R/data_plot.R b/R/data_plot.R
index 9afa86843..3b916383f 100644
--- a/R/data_plot.R
+++ b/R/data_plot.R
@@ -67,10 +67,6 @@
 #' x <- hdi(model)
 #' plot(x) + theme_modern()
 #'
-#' data <- rnorm(1000, 1)
-#' x <- p_direction(data)
-#' plot(x)
-#'
 #' x <- p_direction(model, verbose = FALSE)
 #' plot(x)
 #'
diff --git a/R/plot.check_outliers.R b/R/plot.check_outliers.R
index 4cf04f5c8..eae2b173f 100644
--- a/R/plot.check_outliers.R
+++ b/R/plot.check_outliers.R
@@ -97,13 +97,13 @@ data_plot.check_outliers <- function(x, data = NULL, rescale_distance = TRUE, ..
   d$Id[d$Outliers == "0"] <- NA
 
   method <- switch(attr(x, "method", exact = TRUE),
-    "cook" = "Cook's Distance",
-    "pareto" = "Pareto",
-    "mahalanobis" = "Mahalanobis Distance",
-    "ics" = "Invariant Coordinate Selection",
-    "mcd" = "Minimum Covariance Determinant",
-    "optics" = "OPTICS",
-    "iforest" = "Isolation Forest",
+    cook = "Cook's Distance",
+    pareto = "Pareto",
+    mahalanobis = "Mahalanobis Distance",
+    ics = "Invariant Coordinate Selection",
+    mcd = "Minimum Covariance Determinant",
+    optics = "OPTICS",
+    iforest = "Isolation Forest",
     "Cook's Distance"
   )
 
diff --git a/R/plot.check_outliers_new.R b/R/plot.check_outliers_new.R
index b8d895dd0..9ade11d2e 100644
--- a/R/plot.check_outliers_new.R
+++ b/R/plot.check_outliers_new.R
@@ -44,7 +44,7 @@
       se = FALSE,
       color = colors[1]
     ) +
-    scale_colour_manual(values = c("OK" = colors[2], "Influential" = colors[3])) +
+    scale_colour_manual(values = c(OK = colors[2], Influential = colors[3])) +
     (if (isTRUE(show_labels)) {
       if (requireNamespace("ggrepel", quietly = TRUE)) {
         ggrepel::geom_text_repel(
diff --git a/R/plot.compare_performance.R b/R/plot.compare_performance.R
index 3db5c7871..c61c42fce 100644
--- a/R/plot.compare_performance.R
+++ b/R/plot.compare_performance.R
@@ -40,10 +40,10 @@ data_plot.compare_performance <- function(x, data = NULL, ...) {
   dataplot$values[dataplot$values > 1] <- 1
 
   attr(dataplot, "info") <- list(
-    "xlab" = "",
-    "ylab" = "",
-    "title" = "Comparison of Model Indices",
-    "legend_color" = "Models"
+    xlab = "",
+    ylab = "",
+    title = "Comparison of Model Indices",
+    legend_color = "Models"
   )
 
   class(dataplot) <- c("data_plot", "see_compare_performance", "data.frame")
diff --git a/R/plot.describe_distribution.R b/R/plot.describe_distribution.R
index 4f3012b72..653c594a0 100644
--- a/R/plot.describe_distribution.R
+++ b/R/plot.describe_distribution.R
@@ -199,7 +199,7 @@ plot.see_parameters_distribution <- function(x,
     }
 
     names(highlight_color) <- highlight
-    highlight_color <- c(highlight_color, "no_highlight" = "grey70")
+    highlight_color <- c(highlight_color, no_highlight = "grey70")
 
     p <- p +
       scale_fill_manual(values = highlight_color) +
diff --git a/R/plot.estimate_contrasts.R b/R/plot.estimate_contrasts.R
index d2f329b89..2dbfbbfeb 100644
--- a/R/plot.estimate_contrasts.R
+++ b/R/plot.estimate_contrasts.R
@@ -16,9 +16,9 @@ data_plot.estimate_contrasts <- function(x, data = NULL, ...) {
   dataplot <- .data_contrasts_and_means(x, means, x_name = x_name, y_name = y_name)
 
   attr(dataplot, "info") <- list(
-    "xlab" = x_name,
-    "ylab" = y_name,
-    "title" = paste0("Estimated ", y_name, "s and Contrasts")
+    xlab = x_name,
+    ylab = y_name,
+    title = paste0("Estimated ", y_name, "s and Contrasts")
   )
 
   class(dataplot) <- c("data_plot", "see_estimate_contrasts", class(dataplot))
@@ -45,9 +45,9 @@ data_plot.estimate_contrasts <- function(x, data = NULL, ...) {
   polygons <- merge(polygons, data_means[c("Level2", "Mean2")], by = "Level2")
 
   polygons <- rbind(
-    cbind(polygons, data.frame("x" = polygons$Level1, "y" = polygons$Mean1)),
-    cbind(polygons, data.frame("x" = polygons$Level2, "y" = polygons$Mean1 - polygons$CI_low)),
-    cbind(polygons, data.frame("x" = polygons$Level2, "y" = polygons$Mean1 - polygons$CI_high))
+    cbind(polygons, data.frame(x = polygons$Level1, y = polygons$Mean1)),
+    cbind(polygons, data.frame(x = polygons$Level2, y = polygons$Mean1 - polygons$CI_low)),
+    cbind(polygons, data.frame(x = polygons$Level2, y = polygons$Mean1 - polygons$CI_high))
   )
 
   list(
diff --git a/R/plot.estimate_density.R b/R/plot.estimate_density.R
index f472bcad7..ad431a8c6 100644
--- a/R/plot.estimate_density.R
+++ b/R/plot.estimate_density.R
@@ -51,11 +51,11 @@ data_plot.estimate_density <- function(x,
 
   attr(dataplot, "summary") <- summary
   attr(dataplot, "info") <- list(
-    "xlab" = "Values",
-    "ylab" = "Density",
-    "legend_fill" = "Parameter",
-    "legend_color" = "Parameter",
-    "title" = "Estimated Density Function"
+    xlab = "Values",
+    ylab = "Density",
+    legend_fill = "Parameter",
+    legend_color = "Parameter",
+    title = "Estimated Density Function"
   )
 
   class(dataplot) <- c("data_plot", "see_estimate_density", class(dataplot))
diff --git a/R/plot.hdi.R b/R/plot.hdi.R
index bab66afe9..03b33e79c 100644
--- a/R/plot.hdi.R
+++ b/R/plot.hdi.R
@@ -121,10 +121,10 @@ data_plot.bayestestR_eti <- data_plot.hdi
   dataplot <- .fix_facet_names(dataplot)
 
   attr(dataplot, "info") <- list(
-    "xlab" = "Possible parameter values",
-    "ylab" = ylab,
-    "legend_fill" = legend_title,
-    "title" = plot_title
+    xlab = "Possible parameter values",
+    ylab = ylab,
+    legend_fill = legend_title,
+    title = plot_title
   )
 
   class(dataplot) <- c("data_plot", "see_hdi", class(dataplot))
diff --git a/man/data_plot.Rd b/man/data_plot.Rd
index 4daef23d7..af31261df 100644
--- a/man/data_plot.Rd
+++ b/man/data_plot.Rd
@@ -81,10 +81,6 @@ plot(x)
 x <- hdi(model)
 plot(x) + theme_modern()
 
-data <- rnorm(1000, 1)
-x <- p_direction(data)
-plot(x)
-
 x <- p_direction(model, verbose = FALSE)
 plot(x)
 
diff --git a/vignettes/bayestestR.Rmd b/vignettes/bayestestR.Rmd
index 9d71a0b88..57cf7b851 100644
--- a/vignettes/bayestestR.Rmd
+++ b/vignettes/bayestestR.Rmd
@@ -66,10 +66,10 @@ theme_set(theme_modern())
 ```{r}
 set.seed(123)
 # model with fixed effects only
-model <- rstanarm::stan_glm(Sepal.Length ~ Petal.Width * Species, data = iris, refresh = 0)
+model <<- rstanarm::stan_glm(Sepal.Length ~ Petal.Width * Species, data = iris, refresh = 0)
 
 # model with fixed and random effects as well as zero-inflation component
-model2 <- insight::download_model("brms_zi_3")
+model2 <<- insight::download_model("brms_zi_3")
 ```
 
 ## Density Estimation
@@ -335,7 +335,13 @@ plot(result) +
 ```
 
 ```{r fig.width=11, fig.height=9}
-result <- equivalence_test(model2, ci = c(0.89, 0.95), effects = "all", component = "all")
+result <- equivalence_test(
+  model2,
+  ci = c(0.89, 0.95),
+  effects = "all",
+  component = "all",
+  verbose = FALSE
+)
 
 result