diff --git a/R/bayesfactor_parameters.R b/R/bayesfactor_parameters.R
index ef9574b88..8e71399b4 100644
--- a/R/bayesfactor_parameters.R
+++ b/R/bayesfactor_parameters.R
@@ -113,54 +113,51 @@
 #' Bayes factor smaller than 1/3 indicates substantial evidence in favor of the
 #' null-model) (\cite{Wetzels et al. 2011}).
 #'
-#' @examples
+#' @examplesIf require("logspline")
 #' library(bayestestR)
-#' if (require("logspline")) {
-#'   prior <- distribution_normal(1000, mean = 0, sd = 1)
-#'   posterior <- distribution_normal(1000, mean = .5, sd = .3)
-#'   (BF_pars <- bayesfactor_parameters(posterior, prior, verbose = FALSE))
+#' prior <- distribution_normal(1000, mean = 0, sd = 1)
+#' posterior <- distribution_normal(1000, mean = .5, sd = .3)
+#' (BF_pars <- bayesfactor_parameters(posterior, prior, verbose = FALSE))
 #'
-#'   as.numeric(BF_pars)
-#' }
+#' as.numeric(BF_pars)
+#'
+#' @examplesIf require("rstanarm") && require("emmeans") && require("logspline")
 #' \donttest{
 #' # rstanarm models
 #' # ---------------
-#' if (require("rstanarm") && require("emmeans") && require("logspline")) {
-#'   contrasts(sleep$group) <- contr.equalprior_pairs # see vingette
-#'   stan_model <- suppressWarnings(stan_lmer(
-#'     extra ~ group + (1 | ID),
-#'     data = sleep,
-#'     refresh = 0
-#'   ))
-#'   bayesfactor_parameters(stan_model, verbose = FALSE)
-#'   bayesfactor_parameters(stan_model, null = rope_range(stan_model))
+#' contrasts(sleep$group) <- contr.equalprior_pairs # see vingette
+#' stan_model <- suppressWarnings(stan_lmer(
+#'   extra ~ group + (1 | ID),
+#'   data = sleep,
+#'   refresh = 0
+#' ))
+#' bayesfactor_parameters(stan_model, verbose = FALSE)
+#' bayesfactor_parameters(stan_model, null = rope_range(stan_model))
 #'
-#'   # emmGrid objects
-#'   # ---------------
-#'   group_diff <- pairs(emmeans(stan_model, ~group, data = sleep))
-#'   bayesfactor_parameters(group_diff, prior = stan_model, verbose = FALSE)
+#' # emmGrid objects
+#' # ---------------
+#' group_diff <- pairs(emmeans(stan_model, ~group, data = sleep))
+#' bayesfactor_parameters(group_diff, prior = stan_model, verbose = FALSE)
 #'
-#'   # Or
-#'   # group_diff_prior <- pairs(emmeans(unupdate(stan_model), ~group))
-#'   # bayesfactor_parameters(group_diff, prior = group_diff_prior, verbose = FALSE)
+#' # Or
+#' # group_diff_prior <- pairs(emmeans(unupdate(stan_model), ~group))
+#' # bayesfactor_parameters(group_diff, prior = group_diff_prior, verbose = FALSE)
 #' }
-#'
+#' @examplesIf require("brms") && require("logspline")
 #' # brms models
 #' # -----------
-#' if (require("brms") && require("logspline")) {
-#'   contrasts(sleep$group) <- contr.equalprior_pairs # see vingette
-#'   my_custom_priors <-
-#'     set_prior("student_t(3, 0, 1)", class = "b") +
-#'     set_prior("student_t(3, 0, 1)", class = "sd", group = "ID")
+#' contrasts(sleep$group) <- contr.equalprior_pairs # see vingette
+#' my_custom_priors <-
+#'   set_prior("student_t(3, 0, 1)", class = "b") +
+#'   set_prior("student_t(3, 0, 1)", class = "sd", group = "ID")
+#'
+#' brms_model <- suppressWarnings(brm(extra ~ group + (1 | ID),
+#'   data = sleep,
+#'   prior = my_custom_priors,
+#'   refresh = 0
+#' ))
+#' bayesfactor_parameters(brms_model, verbose = FALSE)
 #'
-#'   brms_model <- suppressWarnings(brm(extra ~ group + (1 | ID),
-#'     data = sleep,
-#'     prior = my_custom_priors,
-#'     refresh = 0
-#'   ))
-#'   bayesfactor_parameters(brms_model, verbose = FALSE)
-#' }
-#' }
 #' @references
 #' \itemize{
 #' \item Wagenmakers, E. J., Lodewyckx, T., Kuriyal, H., and Grasman, R. (2010).
diff --git a/man/bayesfactor_parameters.Rd b/man/bayesfactor_parameters.Rd
index 1eb285199..b9904d92b 100644
--- a/man/bayesfactor_parameters.Rd
+++ b/man/bayesfactor_parameters.Rd
@@ -260,53 +260,52 @@ null-model) (\cite{Wetzels et al. 2011}).
 }
 
 \examples{
+\dontshow{if (require("logspline")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 library(bayestestR)
-if (require("logspline")) {
-  prior <- distribution_normal(1000, mean = 0, sd = 1)
-  posterior <- distribution_normal(1000, mean = .5, sd = .3)
-  (BF_pars <- bayesfactor_parameters(posterior, prior, verbose = FALSE))
+prior <- distribution_normal(1000, mean = 0, sd = 1)
+posterior <- distribution_normal(1000, mean = .5, sd = .3)
+(BF_pars <- bayesfactor_parameters(posterior, prior, verbose = FALSE))
 
-  as.numeric(BF_pars)
-}
+as.numeric(BF_pars)
+\dontshow{\}) # examplesIf}
+\dontshow{if (require("rstanarm") && require("emmeans") && require("logspline")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 \donttest{
 # rstanarm models
 # ---------------
-if (require("rstanarm") && require("emmeans") && require("logspline")) {
-  contrasts(sleep$group) <- contr.equalprior_pairs # see vingette
-  stan_model <- suppressWarnings(stan_lmer(
-    extra ~ group + (1 | ID),
-    data = sleep,
-    refresh = 0
-  ))
-  bayesfactor_parameters(stan_model, verbose = FALSE)
-  bayesfactor_parameters(stan_model, null = rope_range(stan_model))
+contrasts(sleep$group) <- contr.equalprior_pairs # see vingette
+stan_model <- suppressWarnings(stan_lmer(
+  extra ~ group + (1 | ID),
+  data = sleep,
+  refresh = 0
+))
+bayesfactor_parameters(stan_model, verbose = FALSE)
+bayesfactor_parameters(stan_model, null = rope_range(stan_model))
 
-  # emmGrid objects
-  # ---------------
-  group_diff <- pairs(emmeans(stan_model, ~group, data = sleep))
-  bayesfactor_parameters(group_diff, prior = stan_model, verbose = FALSE)
+# emmGrid objects
+# ---------------
+group_diff <- pairs(emmeans(stan_model, ~group, data = sleep))
+bayesfactor_parameters(group_diff, prior = stan_model, verbose = FALSE)
 
-  # Or
-  # group_diff_prior <- pairs(emmeans(unupdate(stan_model), ~group))
-  # bayesfactor_parameters(group_diff, prior = group_diff_prior, verbose = FALSE)
+# Or
+# group_diff_prior <- pairs(emmeans(unupdate(stan_model), ~group))
+# bayesfactor_parameters(group_diff, prior = group_diff_prior, verbose = FALSE)
 }
-
+\dontshow{\}) # examplesIf}
+\dontshow{if (require("brms") && require("logspline")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 # brms models
 # -----------
-if (require("brms") && require("logspline")) {
-  contrasts(sleep$group) <- contr.equalprior_pairs # see vingette
-  my_custom_priors <-
-    set_prior("student_t(3, 0, 1)", class = "b") +
-    set_prior("student_t(3, 0, 1)", class = "sd", group = "ID")
+contrasts(sleep$group) <- contr.equalprior_pairs # see vingette
+my_custom_priors <-
+  set_prior("student_t(3, 0, 1)", class = "b") +
+  set_prior("student_t(3, 0, 1)", class = "sd", group = "ID")
 
-  brms_model <- suppressWarnings(brm(extra ~ group + (1 | ID),
-    data = sleep,
-    prior = my_custom_priors,
-    refresh = 0
-  ))
-  bayesfactor_parameters(brms_model, verbose = FALSE)
-}
-}
+brms_model <- suppressWarnings(brm(extra ~ group + (1 | ID),
+  data = sleep,
+  prior = my_custom_priors,
+  refresh = 0
+))
+bayesfactor_parameters(brms_model, verbose = FALSE)
+\dontshow{\}) # examplesIf}
 }
 \references{
 \itemize{
diff --git a/man/sensitivity_to_prior.Rd b/man/sensitivity_to_prior.Rd
index 3602bee73..99da2ac3a 100644
--- a/man/sensitivity_to_prior.Rd
+++ b/man/sensitivity_to_prior.Rd
@@ -30,26 +30,19 @@ antagonistic prior (a prior of same shape located on the opposite of the
 effect).
 }
 \examples{
+\dontshow{if (require("rstanarm")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 \donttest{
 library(bayestestR)
 
 # rstanarm models
 # -----------------------------------------------
-if (require("rstanarm")) {
-  model <- rstanarm::stan_glm(mpg ~ wt, data = mtcars)
-  sensitivity_to_prior(model)
+model <- rstanarm::stan_glm(mpg ~ wt, data = mtcars)
+sensitivity_to_prior(model)
 
-  model <- rstanarm::stan_glm(mpg ~ wt + cyl, data = mtcars)
-  sensitivity_to_prior(model, index = c("Median", "MAP"))
-}
-
-# brms models
-# -----------------------------------------------
-if (require("brms")) {
-  model <- brms::brm(mpg ~ wt + cyl, data = mtcars)
-  # sensitivity_to_prior(model)
-}
+model <- rstanarm::stan_glm(mpg ~ wt + cyl, data = mtcars)
+sensitivity_to_prior(model, index = c("Median", "MAP"))
 }
+\dontshow{\}) # examplesIf}
 }
 \seealso{
 DescTools