diff --git a/DESCRIPTION b/DESCRIPTION
index c1037d08..f0bab48e 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: correlation
 Title: Methods for Correlation Analysis
-Version: 0.7.0
+Version: 0.7.1
 Authors@R: 
     c(person(given = "Dominique",
              family = "Makowski",
diff --git a/NEWS.md b/NEWS.md
index c8a44e3b..fe893e67 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,9 @@
+# correlation 0.7.1
+
+## Bug Fixes
+
+- Bug fix in `plot()` methods
+
 # correlation 0.7.0
 
 ## Breaking Changes
diff --git a/R/visualisation_recipe.cor_test.R b/R/visualisation_recipe.cor_test.R
index c8a46752..3688c4ce 100644
--- a/R/visualisation_recipe.cor_test.R
+++ b/R/visualisation_recipe.cor_test.R
@@ -70,7 +70,7 @@ visualisation_recipe.easycor_test <- function(x,
   }
 
   # Out
-  class(layers) <- c("visualisation_recipe", class(layers))
+  class(layers) <- c("visualisation_recipe", "see_visualisation_recipe", class(layers))
   attr(layers, "data") <- data
   layers
 }
diff --git a/R/visualisation_recipe.easycormatrix.R b/R/visualisation_recipe.easycormatrix.R
index 5e1f7f47..9a0b9380 100644
--- a/R/visualisation_recipe.easycormatrix.R
+++ b/R/visualisation_recipe.easycormatrix.R
@@ -132,7 +132,7 @@ visualisation_recipe.easycormatrix <- function(x,
   layers[[paste0("l", l)]] <- .visualisation_easycormatrix_labs(labs)
 
   # Out
-  class(layers) <- c("visualisation_recipe", class(layers))
+  class(layers) <- c("visualisation_recipe", "see_visualisation_recipe", class(layers))
   attr(layers, "data") <- data
   layers
 
diff --git a/man/cor_smooth.Rd b/man/cor_smooth.Rd
index 1c51033a..fce5481a 100644
--- a/man/cor_smooth.Rd
+++ b/man/cor_smooth.Rd
@@ -8,9 +8,9 @@
 \usage{
 cor_smooth(x, method = "psych", verbose = TRUE, ...)
 
-is.positive_definite(x, tol = .Machine$double.eps, ...)
+is.positive_definite(x, tol = 10^-12, ...)
 
-is_positive_definite(x, tol = .Machine$double.eps, ...)
+is_positive_definite(x, tol = 10^-12, ...)
 }
 \arguments{
 \item{x}{A correlation matrix.}
@@ -21,7 +21,7 @@ is_positive_definite(x, tol = .Machine$double.eps, ...)
 
 \item{...}{Other arguments to be passed to or from other functions.}
 
-\item{tol}{The minimum eigen values to be considered as acceptable.}
+\item{tol}{The minimum eigenvalue to be considered as acceptable.}
 }
 \description{
 Make correlations positive definite using \code{psych::cor.smooth}.
diff --git a/man/cor_test.Rd b/man/cor_test.Rd
index f2fe972c..9396cd82 100644
--- a/man/cor_test.Rd
+++ b/man/cor_test.Rd
@@ -41,7 +41,8 @@ correlation) or \code{"shepherd"} (for Shepherd's Pi correlation). Setting
 \code{"auto"} will attempt at selecting the most relevant method
 (polychoric when ordinal factors involved, tetrachoric when dichotomous
 factors involved, point-biserial if one dichotomous and one continuous and
-pearson otherwise).}
+pearson otherwise). See below the \strong{details} section for a desription of
+these indices.}
 
 \item{ci}{Confidence/Credible Interval level. If \code{"default"}, then it is
 set to \code{0.95} (\verb{95\%} CI).}
@@ -128,7 +129,7 @@ Bishara and Hittner, 2017).
 \item \strong{Biweight midcorrelation}: A measure of similarity that is
 median-based, instead of the traditional mean-based, thus being less
 sensitive to outliers. It can be used as a robust alternative to other
-similarity metrics, such as Pearson correlation (Langfelder \& Horvath,
+similarity metrics, such as Pearson correlation (Langfelder & Horvath,
 2012).
 
 \item \strong{Distance correlation}: Distance correlation measures both
@@ -147,7 +148,7 @@ distance).
 \item \strong{Blomqvist’s coefficient}: The Blomqvist’s coefficient (also
 referred to as Blomqvist's Beta or medial correlation; Blomqvist, 1950) is a
 median-based non-parametric correlation that has some advantages over
-measures such as Spearman's or Kendall's estimates (see Shmid and Schimdt,
+measures such as Spearman's or Kendall's estimates (see Shmid & Schimdt,
 2006).
 
 \item \strong{Hoeffding’s D}: The Hoeffding’s D statistics is a
diff --git a/man/cor_to_p.Rd b/man/cor_to_p.Rd
index 4df40bef..d9ed0f17 100644
--- a/man/cor_to_p.Rd
+++ b/man/cor_to_p.Rd
@@ -28,7 +28,8 @@ correlation) or \code{"shepherd"} (for Shepherd's Pi correlation). Setting
 \code{"auto"} will attempt at selecting the most relevant method
 (polychoric when ordinal factors involved, tetrachoric when dichotomous
 factors involved, point-biserial if one dichotomous and one continuous and
-pearson otherwise).}
+pearson otherwise). See below the \strong{details} section for a desription of
+these indices.}
 
 \item{correction}{Only used if method is 'spearman' or 'kendall'. Can be
 'fieller' (default; Fieller et al., 1957), 'bw' (only for Spearman) or
diff --git a/man/correlation.Rd b/man/correlation.Rd
index ff12f90d..ed8b5483 100644
--- a/man/correlation.Rd
+++ b/man/correlation.Rd
@@ -63,7 +63,8 @@ correlation) or \code{"shepherd"} (for Shepherd's Pi correlation). Setting
 \code{"auto"} will attempt at selecting the most relevant method
 (polychoric when ordinal factors involved, tetrachoric when dichotomous
 factors involved, point-biserial if one dichotomous and one continuous and
-pearson otherwise).}
+pearson otherwise). See below the \strong{details} section for a desription of
+these indices.}
 
 \item{p_adjust}{Correction method for frequentist correlations. Can be one of
 \code{"holm"} (default), \code{"hochberg"}, \code{"hommel"},
@@ -181,7 +182,7 @@ Bishara and Hittner, 2017).
 \item \strong{Biweight midcorrelation}: A measure of similarity that is
 median-based, instead of the traditional mean-based, thus being less
 sensitive to outliers. It can be used as a robust alternative to other
-similarity metrics, such as Pearson correlation (Langfelder \& Horvath,
+similarity metrics, such as Pearson correlation (Langfelder & Horvath,
 2012).
 
 \item \strong{Distance correlation}: Distance correlation measures both
@@ -200,7 +201,7 @@ distance).
 \item \strong{Blomqvist’s coefficient}: The Blomqvist’s coefficient (also
 referred to as Blomqvist's Beta or medial correlation; Blomqvist, 1950) is a
 median-based non-parametric correlation that has some advantages over
-measures such as Spearman's or Kendall's estimates (see Shmid and Schimdt,
+measures such as Spearman's or Kendall's estimates (see Shmid & Schimdt,
 2006).
 
 \item \strong{Hoeffding’s D}: The Hoeffding’s D statistics is a