diff --git a/R/equivalence_test.R b/R/equivalence_test.R
index b72475009..df88a0d79 100644
--- a/R/equivalence_test.R
+++ b/R/equivalence_test.R
@@ -31,11 +31,11 @@ bayestestR::equivalence_test
 #' In classical null hypothesis significance testing (NHST) within a frequentist
 #' framework, it is not possible to accept the null hypothesis, H0 - unlike
 #' in Bayesian statistics, where such probability statements are possible.
-#' \dQuote{[...] one can only reject the null hypothesis if the test
+#' "[...] one can only reject the null hypothesis if the test
 #' statistics falls into the critical region(s), or fail to reject this
 #' hypothesis. In the latter case, all we can say is that no significant effect
-#' was observed, but one cannot conclude that the null hypothesis is true.}
-#' (\cite{Pernet 2017}). One way to address this issues without Bayesian methods
+#' was observed, but one cannot conclude that the null hypothesis is true."
+#' (_Pernet 2017_). One way to address this issues without Bayesian methods
 #' is *Equivalence Testing*, as implemented in `equivalence_test()`.
 #' While you either can reject the null hypothesis or claim an inconclusive result
 #' in NHST, the equivalence test - according to _Pernet_ - adds a third category,
@@ -50,9 +50,8 @@ bayestestR::equivalence_test
 #' ## Calculation of equivalence testing
 #' - "bayes" - Bayesian rule (Kruschke 2018)
 #'
-#'   This rule follows the \dQuote{HDI+ROPE decision rule} \cite{(Kruschke,
-#'   2014, 2018)} used for the
-#'   [`Bayesian counterpart()`][bayestestR::equivalence_test]. This
+#'   This rule follows the "HDI+ROPE decision rule" (_Kruschke, 2014, 2018_) used
+#'   for the [`Bayesian counterpart()`][bayestestR::equivalence_test]. This
 #'   means, if the confidence intervals are completely outside the ROPE, the
 #'   "null hypothesis" for this parameter is "rejected". If the ROPE
 #'   completely covers the CI, the null hypothesis is accepted. Else, it's
diff --git a/man/equivalence_test.lm.Rd b/man/equivalence_test.lm.Rd
index 31aba2db9..c02207df5 100644
--- a/man/equivalence_test.lm.Rd
+++ b/man/equivalence_test.lm.Rd
@@ -70,11 +70,11 @@ Compute the (conditional) equivalence test for frequentist models.
 In classical null hypothesis significance testing (NHST) within a frequentist
 framework, it is not possible to accept the null hypothesis, H0 - unlike
 in Bayesian statistics, where such probability statements are possible.
-\dQuote{\link{...} one can only reject the null hypothesis if the test
+"\link{...} one can only reject the null hypothesis if the test
 statistics falls into the critical region(s), or fail to reject this
 hypothesis. In the latter case, all we can say is that no significant effect
-was observed, but one cannot conclude that the null hypothesis is true.}
-(\cite{Pernet 2017}). One way to address this issues without Bayesian methods
+was observed, but one cannot conclude that the null hypothesis is true."
+(\emph{Pernet 2017}). One way to address this issues without Bayesian methods
 is \emph{Equivalence Testing}, as implemented in \code{equivalence_test()}.
 While you either can reject the null hypothesis or claim an inconclusive result
 in NHST, the equivalence test - according to \emph{Pernet} - adds a third category,
@@ -89,9 +89,8 @@ results returned from the equivalence test.
 \itemize{
 \item "bayes" - Bayesian rule (Kruschke 2018)
 
-This rule follows the \dQuote{HDI+ROPE decision rule} \cite{(Kruschke,
-2014, 2018)} used for the
-\code{\link[bayestestR:equivalence_test]{Bayesian counterpart()}}. This
+This rule follows the "HDI+ROPE decision rule" (\emph{Kruschke, 2014, 2018}) used
+for the \code{\link[bayestestR:equivalence_test]{Bayesian counterpart()}}. This
 means, if the confidence intervals are completely outside the ROPE, the
 "null hypothesis" for this parameter is "rejected". If the ROPE
 completely covers the CI, the null hypothesis is accepted. Else, it's
diff --git a/man/model_parameters.BFBayesFactor.Rd b/man/model_parameters.BFBayesFactor.Rd
index c16514916..328e25f3d 100644
--- a/man/model_parameters.BFBayesFactor.Rd
+++ b/man/model_parameters.BFBayesFactor.Rd
@@ -69,7 +69,7 @@ cell proportions/counts for Bayesian contingency table analysis (from
 \code{BayesFactor::contingencyTableBF()}). Defaults to \code{FALSE}, as this
 information is often redundant.}
 
-\item{verbose}{Toggle warnings and messages.}
+\item{verbose}{Toggle off warnings.}
 
 \item{cohens_d, cramers_v}{Deprecated. Please use \code{effectsize_type}.}