diff --git a/.gitignore b/.gitignore
index 8620c310..52d77690 100644
--- a/.gitignore
+++ b/.gitignore
@@ -30,3 +30,4 @@ coverage.*
 .vscode/
 .rds
 node_modules
+vintage_NAMESPACE
diff --git a/NAMESPACE b/NAMESPACE
index 5ad2b34d..1b06e70d 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -6,7 +6,6 @@ export(dbetaMix)
 export(dbetabinom)
 export(dbetabinomMix)
 export(dbetadiff)
-export(myPlotDiff)
 export(oc2)
 export(oc3)
 export(ocPostprob)
@@ -18,6 +17,7 @@ export(ocRctPredprobDist)
 export(pbetaMix)
 export(pbetadiff)
 export(plotBeta)
+export(plotBetaDiff)
 export(plotBounds)
 export(plotDecision)
 export(plotOc)
diff --git a/R/boundsPostprob.R b/R/boundsPostprob.R
index a35fef8d..9cf86fe5 100644
--- a/R/boundsPostprob.R
+++ b/R/boundsPostprob.R
@@ -2,7 +2,7 @@
 #'
 #' This function is used to identify the efficacy and futility
 #' boundaries based on the following rules:
-#' Efficacy boundary: find minimum x (xU) where Pr(RR > p1 |x, n, a, b) >= tU and
+#' Efficacy boundary: find minimum x (xU) where Pr(RR > p1 | x, n, a, b) >= tU and
 #' Futility boundary: find maximum x (xL) where Pr(RR < p0 | x, n, a, b) >= tL
 #'
 #' @inheritParams postprob
@@ -48,12 +48,12 @@ boundsPostprob <- function(looks, p0, p1 = p0, tL, tU, parE = c(1, 1), weights)
     xL <- NA
     xU <- NA
     for (x in 0:n) {
-      postp_fut <- 1 - postprob(x, n, p0, parE, weights) # futility look
+      postp_fut <- 1 - postprob(x = x, n = n, p = p0, parE = parE, weights = weights) # futility look
       if (postp_fut >= tL) { # Rule is P(RR < p0) > tL
         postL <- postp_fut
         xL <- x
       }
-      postp_eff <- postprob(x, n, p1, parE, weights) # efficacy look
+      postp_eff <- postprob(x = x, n = n, p = p1, parE = parE, weights = weights) # efficacy look
       if (postp_eff >= tU) { # Rule is P(RR > p1) > tU
         postU <- postp_eff
         xU <- x
diff --git a/R/plotBeta.R b/R/plotBeta.R
index 98a6788c..d4d71a77 100644
--- a/R/plotBeta.R
+++ b/R/plotBeta.R
@@ -2,11 +2,11 @@
 #'
 #' This function will plot the PDF of a beta distribution
 #'
+#' @inheritParams dbetabinom
 #' @typed alpha : number
 #'  first parameter of the Beta distribution
 #' @typed beta : number
 #'  second parameter of the Beta distribution
-#'
 #' @return A beta distribution density plot
 #'
 #' @importFrom graphics axis
@@ -14,7 +14,7 @@
 #' @example examples/plotBeta.R
 #' @export
 #' @keywords graphics
-plotBeta <- function(alpha, beta) {
+plotBeta <- function(alpha, beta, ...) {
   x_support <- seq(from = 0, to = 1, length = 1000)
   data <- data.frame(
     grid = x_support,
@@ -30,141 +30,87 @@ plotBeta <- function(alpha, beta) {
     ggplot2::scale_x_continuous(labels = scales::percent_format())
 }
 
-#' Plot Diff Between two Beta distributions
+#' Plot difference Between two Beta distributions
 #'
 #' This function will plot the PDF of a difference between two Beta distributions
 #'
-#' @param parY non-negative parameters of the treatment Beta distribution.
-#' @param parX non-negative parameters of the historical control Beta distribution
-#' @param cut_B a meaningful improvement threshold
-#' @param cut_W a poor improvement throshold
-#' @param shade paint the two areas under the curve, default value=1 as "yes". other numbers stands for "no";
-#' @param note show values of the colored area, default value=1 as "yes". other numbers stands for "no"
-#' @param \dots additional arguments to \code{plot}
-#' @return nothing, only produces the plot as side effect
+#' @typed parY : numeric
+#'  non-negative parameters of the treatment Beta distribution.
+#' @typed parX : numeric
+#'  non-negative parameters of the historical control Beta distribution
+#' @typed cut_B : number
+#'  a meaningful improvement threshold, the lower boundary of a meaningfully improvement in response rate
+#' @typed cut_W : number
+#'  a poor improvement threshold, the upper boundary of a meaningfully poor improvement in response rate
+#' @typed shade : flag
+#'  paint the two areas under the curve, default value = TRUE
+#' @typed note : flag
+#'  show values of the colored area, default value = TRUE
+#' @typed ... :
+#'  additional arguments to `ggplot()`
+#' @return a ggplot object
 #'
-#' @example examples/myPlotDiff.R
+#' @example examples/plotBetaDiff.R
 #'
 #' @importFrom graphics par axis polygon mtext
 #' @importFrom stats integrate
 #'
 #' @export
 #' @keywords graphics
-myPlotDiff <- function(parY, # parameters of phase Ib trial;
-                       parX, # parameters of HC;
-                       cut_B = 0.20, # a meaningful improvement threshold;
-                       cut_W = 0.1, # a poor improvement threshold;
-                       shade = 1, # paint the two areas under the curve, default: yes. other numbers stands for "no";
-                       note = 1, # show values of the colored area, default: yes. other numbers stands for "no";
-                       ...) {
-  if (note == 1) {
-    graphics::par(mar = c(5, 15, 1, 15) + .1)
-  } else {
-    graphics::par(mar = c(5, 5, 1, 5) + .1)
-  }
-  grid <- seq(from = -0.5, to = 0.75, length = 1000)
-  xticks <- seq(from = -1, to = 1, by = 0.25)
-
-
-
-  graphics::plot(
-    x = grid,
-    y = dbetadiff(grid, parY = parY, parX = parX),
-    ylab = "",
-    xaxt = "n",
-    yaxt = "n",
-    type = "l",
-    xaxs = "i",
-    yaxs = "i",
-    ...
+plotBetaDiff <- function(parY, # parameters of experimental arm
+                         parX, # parameters of control or SOC
+                         Go_cut = 0.20, # a meaningful improvement threshold
+                         Stop_cut = 0.1, # a poor improvement threshold
+                         shade = TRUE, # paint the two areas under the curve
+                         note = TRUE) { # show values of the colored area
+  diff <- seq(from = -1, to = 1, length = 1000)
+  data <- data.frame(
+    grid = diff,
+    density = dbetadiff(z = diff, parY = parY, parX = parX)
   )
+  data$Stop <- ifelse(diff > -1 & diff < Stop_cut, TRUE, FALSE)
+  data$Go <- ifelse(diff > Go_cut & diff < 1, TRUE, FALSE)
 
-  graphics::axis(
-    side = 1, at = xticks,
-    labels =
-      paste(ifelse(xticks >= 0, "+", ""),
-        xticks * 100, "%",
-        sep = ""
-      )
+  Go_auc <- integrate(
+    f = dbetadiff,
+    parY = parY,
+    parX = parX,
+    lower = Go_cut, # Calculate probability of Go, if difference was at least `Go_cut`.
+    upper = 1
+  )
+  Stop_auc <- integrate(
+    f = dbetadiff,
+    parY = parY,
+    parX = parX,
+    lower = -1,
+    upper = Stop_cut # Calculate probability of Stop, if difference was at most `Stop_cut`.
   )
 
-  ## now color the go / stop prob areas
-
-  if (shade == 1) {
-    ## first stop:
-    stopGrid <- grid[grid <= cut_W]
-    nStop <- length(stopGrid)
-
-    graphics::polygon(
-      x =
-        c(
-          stopGrid,
-          rev(stopGrid)
-        ),
-      y =
-        c(
-          rep(0, nStop),
-          dbetadiff(rev(stopGrid), parY = parY, parX = parX)
-        ),
-      col = "red"
-    )
-
-    A_value <- stats::integrate(
-      f = dbetadiff,
-      parY = parY,
-      parX = parX,
-      lower = -1,
-      upper = cut_W
-    )
-    if (note == 1) {
-      graphics::mtext(
-        paste("Prob(diff< ", round(cut_W * 100), "%)=",
-          sprintf("%1.2f%%", 100 * as.numeric(A_value$value)),
-          sep = ""
-        ),
-        side = 2, line = 1, las = 1, cex = 1
-      )
-    }
-
-    ## then go:
-    goGrid <- grid[grid >= cut_B]
-    nGo <- length(goGrid)
-
-    graphics::polygon(
-      x =
-        c(
-          goGrid,
-          rev(goGrid)
-        ),
-      y =
-        c(
-          rep(0, nGo),
-          dbetadiff(rev(goGrid), parY = parY, parX = parX)
-        ),
-      col = "green"
-    )
-
-    B_value <- stats::integrate(
-      f = dbetadiff,
-      parY = parY,
-      parX = parX,
-      lower = cut_B,
-      upper = 1
-    )
+  Go_label <- paste("P(Go) is", round(Go_auc$value * 100, digits = 2), "%")
+  Stop_label <- paste("P(S) is", round(Stop_auc$value * 100, digits = 2), "%")
+  plot_title <- paste("According to Beta difference density", Go_label, "and", Stop_label)
 
-    if (note == 1) {
-      graphics::mtext(
-        paste(
-          sprintf("%1.2f%%", 100 * as.numeric(B_value$value)),
-          "=Prob(diff> ",
-          round(cut_B * 100), "%)",
-          sep = ""
-        ),
-        side = 4,
-        line = 1,
-        las = 1,
-        cex = 1
-      )
-    }
+  if (shade == TRUE) {
+    pbetadiff_plot <- ggplot2::ggplot(data = data, aes(x = grid, y = density)) +
+      ggplot2::geom_line(colour = "#888888") +
+      geom_area(data = data[data$grid < Stop_cut,], fill = "#FF0046",
+                mapping = aes(x = ifelse(grid < 0.2 & grid < 0.5, grid, 0))) +
+      geom_area(data = data[data$grid > Go_cut,], fill = "#009E73",
+                mapping = aes(x = ifelse(grid > 0.3, grid, 0)))  +
+      xlab("Difference between treatment") +
+      ggplot2::ylab(quote(f(x))) +
+      ggplot2::ggtitle(plot_title)
+  } else {
+    pbetadiff_plot <- ggplot2::ggplot(data = data, aes(x = grid, y = density)) +
+      ggplot2::geom_line(colour = "#888888") +
+      xlab("Difference between treatment") +
+      ggplot2::ylab(quote(f(x))) +
+      ggplot2::ggtitle(plot_title)
+  }
+  if (note == TRUE) {
+    pbetadiff_plot <- pbetadiff_plot +
+      ggplot2::annotate("text", x = -0.5, y = 3.75, size = 5, label = Stop_label, colour = "#FF0046") +
+      ggplot2::annotate("text", x = -0.5, y = 3.25, size = 5, label = Go_label, colour = "#009E73")
   }
+  pbetadiff_plot
 }
diff --git a/R/plotOc.R b/R/plotOc.R
index c4765cdd..9806db9a 100644
--- a/R/plotOc.R
+++ b/R/plotOc.R
@@ -1,9 +1,10 @@
 #' Display the operating characteristics using an oc object
 #'
-#' Reads results from \code{\link{ocPredprob}}, \code{\link{ocPostprob}}
+#' Reads results from [ocPredprob()]
 #' etc. and displays a bar plot of the operating characteristics
 #'
-#' @param z returned oc value
+#' @typed oc : list
+#' returned oc parameters
 #' @return nothing, only plots as side effect
 #'
 #' @importFrom graphics barplot title
@@ -11,9 +12,25 @@
 #' @example examples/plotOc.R
 #' @export
 #' @keywords graphics
-plotOc <- function(z) {
+plotOc <- function(oc) {
+
+  if (wiggle == FALSE) {
+    data <-  table(oc$Decision, oc$SampleSize) / oc$params$sim
+  } else {
+
+  }
+
+ggplot(oc, aes(x = name, y = value)) +
+  geom_bar(stat = "identity") +
+  ggtitle("Percentage of trials that Go and Stop per look") +
+  ylabs("Percentage %") +
+  xlabs("Looks and sample size")
+
+
+
   ## plot function for oc.predprob or oc.postprob, or the dist versions of them
-  graphics::barplot(table(z$Decision, z$SampleSize) / z$params$sim, beside = TRUE)
+  graphics::barplot(table(oc$Decision, oc$SampleSize) / oc$params$sim, beside = TRUE)
+
 
   ## get the parameter
   parDat <- lapply(z$params, deparse)
diff --git a/examples/myPlotDiff.R b/examples/myPlotDiff.R
deleted file mode 100644
index c9a4795e..00000000
--- a/examples/myPlotDiff.R
+++ /dev/null
@@ -1,8 +0,0 @@
-myPlotDiff(
-  parY = c(5, 10),
-  parX = c(2, 5),
-  cut_B = 0.2, # a meaningful improvement threshold
-  cut_W = 0.05, # a poor improvement threshold
-  shade = 1, # paint the two areas under the curve, default: yes. other numbers stands for "no";
-  note = 0
-) # show values of the colored area, default: yes. other numbers stands for "no";
diff --git a/examples/plotBeta.R b/examples/plotBeta.R
index 6e84087b..712b5482 100644
--- a/examples/plotBeta.R
+++ b/examples/plotBeta.R
@@ -1,2 +1,3 @@
+# plotBeta
 plotBeta(alpha = 4, beta = 5)
 plotBeta(alpha = 1, beta = 1)
diff --git a/examples/plotBetaDiff.R b/examples/plotBetaDiff.R
new file mode 100644
index 00000000..277e175e
--- /dev/null
+++ b/examples/plotBetaDiff.R
@@ -0,0 +1,23 @@
+# The beta distribution and acceptable bounds for
+# a meaningful improvement of 0.20 and worsening of 0.1
+parX <- c(1, 52) # prior  parameters of experimental arm
+parY <- c(5.5, 20.5) # prior  parameters of control or SOC
+plotBetaDiff(
+  parY = parY,
+  parX = parX,
+  Go_cut = 0.3,
+  Stop_cut = 0.1, # below a difference of 10%, is an unsuccesful trial
+  shade = TRUE,
+  note = TRUE
+)
+
+
+# a larger Go_cut with uniform prior
+plotBetaDiff(
+  parY = c(1, 1), # prior  parameters for experimental arm
+  parX = c(1, 1), # prior parameters for control or SOC arm
+  Go_cut = 0.3,
+  Stop_cut = 0.1, # below a difference of 10%, is an unsuccesful trial
+  shade = TRUE,
+  note = TRUE
+)
diff --git a/examples/plotOc.R b/examples/plotOc.R
index 930ca464..53216078 100644
--- a/examples/plotOc.R
+++ b/examples/plotOc.R
@@ -1,9 +1,16 @@
 # get operating character result from oc.postprob
 
-res1 <- ocPostprob(
+oc <- ocPostprob(
   nnE = c(10, 20, 30), truep = 0.4, p0 = 0.2,
-  p1 = 0.3, tL = 0.6, tU = 0.8, parE = c(1, 1), sim = 50000
+  p1 = 0.3, tL = 0.6, tU = 0.8, parE = c(1, 1), sim = 100, wiggle = FALSE
 )
-res1$oc
+oc$oc
+# plotOc(oc)
+
+
+oc <- ocPostprob(
+  nnE = c(10, 20, 30), truep = 0.4, p0 = 0.2,
+  p1 = 0.3, tL = 0.6, tU = 0.8, parE = c(1, 1), sim = 100, wiggle = TRUE
+)
+oc$oc
 
-plotOc(res1)
diff --git a/inst/WORDLIST b/inst/WORDLIST
index 2faf53fe..be3cf716 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -102,6 +102,7 @@ gelman
 Gelman
 generalizable
 geq
+ggplot
 grayzone
 grey
 Gsponer
@@ -201,6 +202,8 @@ renewcommand
 reproducibility
 responder
 responders
+roxygen
+Roxygen
 Sabanes
 sabanes
 Sabanés
@@ -243,6 +246,7 @@ USUBJID
 VAD
 vanillaBayes
 vanillaPP
+vbump
 Vehtari
 WeightedBayes
 weightedBetaPrior
diff --git a/man/boundsPostprob.Rd b/man/boundsPostprob.Rd
index b21240cd..1fa8bde4 100644
--- a/man/boundsPostprob.Rd
+++ b/man/boundsPostprob.Rd
@@ -40,7 +40,7 @@ binomial test.
 \description{
 This function is used to identify the efficacy and futility
 boundaries based on the following rules:
-Efficacy boundary: find minimum x (xU) where Pr(RR > p1 |x, n, a, b) >= tU and
+Efficacy boundary: find minimum x (xU) where Pr(RR > p1 | x, n, a, b) >= tU and
 Futility boundary: find maximum x (xL) where Pr(RR < p0 | x, n, a, b) >= tL
 }
 \examples{
diff --git a/man/myPlotDiff.Rd b/man/myPlotDiff.Rd
deleted file mode 100644
index 8d949d11..00000000
--- a/man/myPlotDiff.Rd
+++ /dev/null
@@ -1,40 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/plotBeta.R
-\name{myPlotDiff}
-\alias{myPlotDiff}
-\title{Plot Diff Between two Beta distributions}
-\usage{
-myPlotDiff(parY, parX, cut_B = 0.2, cut_W = 0.1, shade = 1, note = 1, ...)
-}
-\arguments{
-\item{parY}{non-negative parameters of the treatment Beta distribution.}
-
-\item{parX}{non-negative parameters of the historical control Beta distribution}
-
-\item{cut_B}{a meaningful improvement threshold}
-
-\item{cut_W}{a poor improvement throshold}
-
-\item{shade}{paint the two areas under the curve, default value=1 as "yes". other numbers stands for "no";}
-
-\item{note}{show values of the colored area, default value=1 as "yes". other numbers stands for "no"}
-
-\item{\dots}{additional arguments to \code{plot}}
-}
-\value{
-nothing, only produces the plot as side effect
-}
-\description{
-This function will plot the PDF of a difference between two Beta distributions
-}
-\examples{
-myPlotDiff(
-  parY = c(5, 10),
-  parX = c(2, 5),
-  cut_B = 0.2, # a meaningful improvement threshold
-  cut_W = 0.05, # a poor improvement threshold
-  shade = 1, # paint the two areas under the curve, default: yes. other numbers stands for "no";
-  note = 0
-) # show values of the colored area, default: yes. other numbers stands for "no";
-}
-\keyword{graphics}
diff --git a/man/plotBeta.Rd b/man/plotBeta.Rd
index bf45b581..a17df369 100644
--- a/man/plotBeta.Rd
+++ b/man/plotBeta.Rd
@@ -4,7 +4,7 @@
 \alias{plotBeta}
 \title{Plot the Beta distribution}
 \usage{
-plotBeta(alpha, beta)
+plotBeta(alpha, beta, ...)
 }
 \arguments{
 \item{alpha}{(\code{number}):\cr first parameter of the Beta distribution}
@@ -18,6 +18,7 @@ A beta distribution density plot
 This function will plot the PDF of a beta distribution
 }
 \examples{
+# plotBeta
 plotBeta(alpha = 4, beta = 5)
 plotBeta(alpha = 1, beta = 1)
 }
diff --git a/man/plotBetaDiff.Rd b/man/plotBetaDiff.Rd
new file mode 100644
index 00000000..ac715de5
--- /dev/null
+++ b/man/plotBetaDiff.Rd
@@ -0,0 +1,62 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plotBeta.R
+\name{plotBetaDiff}
+\alias{plotBetaDiff}
+\title{Plot difference Between two Beta distributions}
+\usage{
+plotBetaDiff(
+  parY,
+  parX,
+  Go_cut = 0.2,
+  Stop_cut = 0.1,
+  shade = TRUE,
+  note = TRUE
+)
+}
+\arguments{
+\item{parY}{(\code{numeric}):\cr non-negative parameters of the treatment Beta distribution.}
+
+\item{parX}{(\code{numeric}):\cr non-negative parameters of the historical control Beta distribution}
+
+\item{shade}{(\code{flag}):\cr paint the two areas under the curve, default value = TRUE}
+
+\item{note}{(\code{flag}):\cr show values of the colored area, default value = TRUE}
+
+\item{cut_B}{(\code{number}):\cr a meaningful improvement threshold, the lower boundary of a meaningfully improvement in response rate}
+
+\item{cut_W}{(\code{number}):\cr a poor improvement threshold, the upper boundary of a meaningfully poor improvement in response rate}
+
+\item{...}{(``):\cr additional arguments to \code{ggplot()}}
+}
+\value{
+a ggplot object
+}
+\description{
+This function will plot the PDF of a difference between two Beta distributions
+}
+\examples{
+# The beta distribution and acceptable bounds for
+# a meaningful improvement of 0.20 and worsening of 0.1
+parX <- c(1, 52) # prior  parameters of experimental arm
+parY <- c(5.5, 20.5) # prior  parameters of control or SOC
+plotBetaDiff(
+  parY = parY,
+  parX = parX,
+  Go_cut = 0.3,
+  Stop_cut = 0.1, # below a difference of 10\%, is an unsuccesful trial
+  shade = TRUE,
+  note = TRUE
+)
+
+
+# a larger Go_cut with uniform prior
+plotBetaDiff(
+  parY = c(1, 1), # prior  parameters for experimental arm
+  parX = c(1, 1), # prior parameters for control or SOC arm
+  Go_cut = 0.3,
+  Stop_cut = 0.1, # below a difference of 10\%, is an unsuccesful trial
+  shade = TRUE,
+  note = TRUE
+)
+}
+\keyword{graphics}
diff --git a/man/plotOc.Rd b/man/plotOc.Rd
index 16389213..76965376 100644
--- a/man/plotOc.Rd
+++ b/man/plotOc.Rd
@@ -4,27 +4,64 @@
 \alias{plotOc}
 \title{Display the operating characteristics using an oc object}
 \usage{
-plotOc(z)
+plotOc(oc)
 }
 \arguments{
-\item{z}{returned oc value}
+\item{oc}{(\code{list}):\cr returned oc parameters}
 }
 \value{
 nothing, only plots as side effect
 }
 \description{
-Reads results from \code{\link{ocPredprob}}, \code{\link{ocPostprob}}
+Reads results from \code{\link[=ocPredprob]{ocPredprob()}}
 etc. and displays a bar plot of the operating characteristics
 }
 \examples{
 # get operating character result from oc.postprob
 
-res1 <- ocPostprob(
+oc <- ocPostprob(
   nnE = c(10, 20, 30), truep = 0.4, p0 = 0.2,
-  p1 = 0.3, tL = 0.6, tU = 0.8, parE = c(1, 1), sim = 50000
+  p1 = 0.3, tL = 0.6, tU = 0.8, parE = c(1, 1), sim = 100, wiggle = FALSE
 )
-res1$oc
+oc$oc
+# plotOc(oc)
 
-plotOc(res1)
+
+oc <- ocPostprob(
+  nnE = c(10, 20, 30), truep = 0.4, p0 = 0.2,
+  p1 = 0.3, tL = 0.6, tU = 0.8, parE = c(1, 1), sim = 100, wiggle = TRUE
+)
+oc$oc
+
+data <- data.frame(Decision = as.factor(oc$Decision),
+           Looks = oc$SampleSize)
+
+table(data$Decision, data$Looks)
+
+data \%>\% group_by(Decision, Looks) \%>\% summarise(n = n())
+
+data \%>\% group_by(SampleSize) \%>\% summarise(n = n())
+
+ggplot(dat, aes(x = SampleSize, y = Decision)) +
+  geom_bar(stat = "identity")
+
+data \%>\% group_by(Looks, Decision) \%>\% summarise(tot = n())
+
+
+table(oc$Decision, oc$SampleSize) / oc$params$sim
+table(oc$Decision, oc$SampleSize)
+
+oc$Decision <- ifelse(oc$Decision == TRUE, "GO",
+                      ifelse(oc$Decision == FALSE, "Stop", "Grey"))
+
+oc$Decision
+
+data.frame(looks = c(res1$wiggled_nnrE))
+
+table(oc$Decision, oc$SampleSize)
+
+tt = data.frame(Decision = res$Decision,
+                look = res$SampleSize)
+tt \%>\% group_by(look) \%>\% summarise(success = per())
 }
 \keyword{graphics}
diff --git a/tests/testthat/test-plotBetaDiff.R b/tests/testthat/test-plotBetaDiff.R
new file mode 100644
index 00000000..e7c2a091
--- /dev/null
+++ b/tests/testthat/test-plotBetaDiff.R
@@ -0,0 +1,22 @@
+# plotBetaDiff
+test_that("plotBetaDiff works as expected", {
+  result <- plotBetaDiff(
+    parY = c(1, 1),
+    parX = c(6, 10),
+    Go_cut = 0.3,
+    Stop_cut = 0.1, # below a difference of 10%, is an unsuccesful trial
+    shade = TRUE,
+    note = TRUE
+  )
+  result <- plotBetaDiff(
+    parY = c(2, 3),
+    parX = c(4, 10),
+    Go_cut = 0.3,
+    Stop_cut = 0.1, # below a difference of 10%, is an unsuccesful trial
+    shade = TRUE,
+    note = TRUE
+  )
+  vdiffr::expect_doppelganger("", result)
+  vdiffr::expect_doppelganger("", result)
+
+})