diff --git a/CRAN-SUBMISSION b/CRAN-SUBMISSION
index f9ec7dee2..2c408c2f4 100644
--- a/CRAN-SUBMISSION
+++ b/CRAN-SUBMISSION
@@ -1,3 +1,3 @@
-Version: 0.22.0
-Date: 2024-06-19 20:40:00 UTC
-SHA: 3861512ee3c11ecca44c2edd412c2a5cb65e1f59
+Version: 0.22.1
+Date: 2024-07-21 11:02:42 UTC
+SHA: 109a438b12d4893ae5b2b86aa058923798a6045a
diff --git a/DESCRIPTION b/DESCRIPTION
index eb54f5beb..81ea45779 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: parameters
 Title: Processing of Model Parameters
-Version: 0.22.0.7
+Version: 0.22.1
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -218,4 +218,3 @@ Config/testthat/edition: 3
 Config/testthat/parallel: true
 Config/Needs/website: easystats/easystatstemplate
 Config/rcmdcheck/ignore-inconsequential-notes: true
-Remotes: easystats/bayestestR
diff --git a/NEWS.md b/NEWS.md
index 6cd3ccab6..edbe49a36 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,13 @@
 # parameters 0.22.1
 
+## Breaking changes
+
+* Revised calculation of the second generation p-value (SGPV) in `equivalence_test()`,
+  which should now be more accurate related to the proportion of the interval
+  that falls inside the ROPE. Formerly, the confidence interval was simply treated
+  as uniformly distributed when calculating the SGPV, now the interval is assumed
+  to be normally distributed.
+
 ## New supported models
 
 * Support for `svy2lme` models from package *svylme*.
diff --git a/R/equivalence_test.R b/R/equivalence_test.R
index 3be162035..f0951e8ac 100644
--- a/R/equivalence_test.R
+++ b/R/equivalence_test.R
@@ -103,7 +103,8 @@ bayestestR::equivalence_test
 #' Second generation p-values (SGPV) were proposed as a statistic that
 #' represents _the proportion of data-supported hypotheses that are also null
 #' hypotheses_ _(Blume et al. 2018, Lakens and Delacre 2020)_. It represents the
-#' proportion of the confidence interval range that is inside the ROPE.
+#' proportion of the confidence interval range (assuming a normally distributed,
+#' equal-tailed interval) that is inside the ROPE.
 #'
 #' ## ROPE range
 #' Some attention is required for finding suitable values for the ROPE limits
@@ -592,10 +593,9 @@ equivalence_test.ggeffects <- function(x,
   data.frame(
     CI_low = final_ci[1],
     CI_high = final_ci[2],
-    SGPV = .sgpv(range_rope, final_ci),
+    SGPV = .rope_coverage(range_rope, final_ci),
     ROPE_low = range_rope[1],
     ROPE_high = range_rope[2],
-    # ROPE_Percentage = .rope_coverage(range_rope, final_ci),
     ROPE_Equivalence = decision,
     stringsAsFactors = FALSE
   )
@@ -606,31 +606,34 @@ equivalence_test.ggeffects <- function(x,
 
 # helper ---------------------
 
-
-.sgpv <- function(rope, ci) {
-  diff_rope <- abs(diff(rope))
+# this function simply takes the length of the range and calculates the proportion
+# of that range that is inside the rope. However, this assumed a "flat", i.e.
+# uniformly distributed interval, which is not accurate for standard confidence
+# intervals. thus, we no longer use this function, but switch to ".rope_coverage()".
+.sgpv <- function(range_rope, ci) {
+  diff_rope <- abs(diff(range_rope))
   diff_ci <- abs(diff(ci))
 
   # inside?
-  if (min(ci) >= min(rope) && max(ci) <= max(rope)) {
+  if (min(ci) >= min(range_rope) && max(ci) <= max(range_rope)) {
     coverage <- 1
 
     # outside?
-  } else if (max(ci) < min(rope) || min(ci) > max(rope)) {
+  } else if (max(ci) < min(range_rope) || min(ci) > max(range_rope)) {
     coverage <- 0
 
     # CI covers completely rope?
-  } else if (max(ci) > max(rope) && min(ci) < min(rope)) {
+  } else if (max(ci) > max(range_rope) && min(ci) < min(range_rope)) {
     coverage <- diff_rope / diff_ci
 
     # CI inside rope and outside max rope?
-  } else if (min(ci) >= min(rope) && max(ci) > max(rope)) {
-    diff_in_rope <- max(rope) - min(ci)
+  } else if (min(ci) >= min(range_rope) && max(ci) > max(range_rope)) {
+    diff_in_rope <- max(range_rope) - min(ci)
     coverage <- diff_in_rope / diff_ci
 
     # CI inside rope and outside min rope?
-  } else if (max(ci) <= max(rope) && min(ci) < min(rope)) {
-    diff_in_rope <- max(ci) - min(rope)
+  } else if (max(ci) <= max(range_rope) && min(ci) < min(range_rope)) {
+    diff_in_rope <- max(ci) - min(range_rope)
     coverage <- diff_in_rope / diff_ci
   }
 
@@ -638,16 +641,27 @@ equivalence_test.ggeffects <- function(x,
 }
 
 
-## FIXME make sure this works for different CI levels
-.rope_coverage <- function(rope, ci_range, ci) {
+# this function simulates a normal distribution, which approximately has the
+# same range / limits as the confidence interval, thus indeed representing a
+# normally distributed confidence interval. We then calculate the probability
+# mass of this interval that is inside the ROPE.
+.rope_coverage <- function(range_rope, ci_range) {
   diff_ci <- abs(diff(ci_range))
   out <- bayestestR::distribution_normal(
     n = 1000,
     mean = ci_range[2] - (diff_ci / 2),
-    sd = diff_ci / 3.28
+    # we divide the complete range by 2, the one-directional range for the SD
+    # then, the range from mean value to lower/upper limit, for a normal
+    # distribution is approximately 3.3 SD (3 SD cover 99.7% of the probability
+    # mass of the normal distribution). Thus, assuming that half of the ci_range
+    # refers to ~ 3.3 SD, we "normalize" the value (i.e. divide by 3.29) to get
+    # the value for one SD, which we need to build the normal distribution.
+    sd = (diff_ci / 2) / 3.29
   )
 
-  rc <- bayestestR::rope(out, range = rope, ci = ci)
+  # The SGPV refers to the proportion of the confidence interval inside the
+  # full ROPE - thus, we set ci = 1 here
+  rc <- bayestestR::rope(out, range = range_rope, ci = 1)
   rc$ROPE_Percentage
 }
 
diff --git a/cran-comments.md b/cran-comments.md
index 5768f7b84..35e40b5f5 100644
--- a/cran-comments.md
+++ b/cran-comments.md
@@ -1 +1 @@
-This release addresses issues with duplicated ORCID in the DESCRIPTION file.
+Maintainance release. Furthermore, this release also fixes an issue with the _datawizard_ dependency on Mac OS X with R (old-release).
diff --git a/man/equivalence_test.lm.Rd b/man/equivalence_test.lm.Rd
index f58df1735..155d2ac51 100644
--- a/man/equivalence_test.lm.Rd
+++ b/man/equivalence_test.lm.Rd
@@ -149,7 +149,8 @@ practical equivalence and accept the alternative hypothesis.
 Second generation p-values (SGPV) were proposed as a statistic that
 represents \emph{the proportion of data-supported hypotheses that are also null
 hypotheses} \emph{(Blume et al. 2018, Lakens and Delacre 2020)}. It represents the
-proportion of the confidence interval range that is inside the ROPE.
+proportion of the confidence interval range (assuming a normally distributed,
+equal-tailed interval) that is inside the ROPE.
 }
 
 \subsection{ROPE range}{
diff --git a/tests/testthat/_snaps/equivalence_test.md b/tests/testthat/_snaps/equivalence_test.md
index 870079898..f8919933a 100644
--- a/tests/testthat/_snaps/equivalence_test.md
+++ b/tests/testthat/_snaps/equivalence_test.md
@@ -10,8 +10,8 @@
       Parameter   |         90% CI |   SGPV | Equivalence |      p
       ------------------------------------------------------------
       (Intercept) | [26.52, 46.86] | < .001 |    Rejected | > .999
-      gear        | [-1.34,  2.07] | 0.354  |   Undecided | 0.578 
+      gear        | [-1.34,  2.07] | 0.648  |   Undecided | 0.578 
       wt          | [-4.47, -1.57] | < .001 |    Rejected | 0.996 
-      cyl         | [-1.94,  0.32] | 0.407  |   Undecided | 0.644 
+      cyl         | [-1.94,  0.32] | 0.270  |   Undecided | 0.644 
       hp          | [-0.05,  0.01] | > .999 |    Accepted | < .001