diff --git a/DESCRIPTION b/DESCRIPTION
index 7bd16232..de86ddb5 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: correlation
 Title: Methods for Correlation Analysis
-Version: 0.8.8
+Version: 0.8.8.1
 Authors@R:
     c(person(given = "Dominique",
              family = "Makowski",
@@ -88,7 +88,7 @@ VignetteBuilder:
     knitr
 Encoding: UTF-8
 Language: en-US
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3
 Roxygen: list(markdown = TRUE)
 Config/testthat/edition: 3
 Config/Needs/website:
diff --git a/NEWS.md b/NEWS.md
index c9759e1c..e583219f 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,11 @@
+# correlation 0.8.9
+
+## Bug Fixes
+
+- `cormatrix_to_excel()` now works correctly with openxlsx2 v1.16+. Fixed
+  conditional formatting rule ordering to accommodate openxlsx2's new waterfall
+  strategy (#361).
+
 # correlation 0.8.8
 
 - `correlation()` gains a `missing=` argument, similar to `stats::cor(use=)`, for controlling how missing data is handled.
diff --git a/R/cormatrix_to_excel.R b/R/cormatrix_to_excel.R
index a4448ef3..d383b5aa 100644
--- a/R/cormatrix_to_excel.R
+++ b/R/cormatrix_to_excel.R
@@ -41,13 +41,17 @@
 #' \dontshow{
 #' setwd(.old_wd)
 #' }
-cormatrix_to_excel <- function(data,
-                               filename,
-                               overwrite = TRUE,
-                               print.mat = TRUE,
-                               ...) {
+cormatrix_to_excel <- function(
+  data,
+  filename,
+  overwrite = TRUE,
+  print.mat = TRUE,
+  ...
+) {
   if (missing(filename)) {
-    insight::format_error("Argument 'filename' required (as per CRAN policies).")
+    insight::format_error(
+      "Argument 'filename' required (as per CRAN policies)."
+    )
   }
 
   insight::check_if_installed("openxlsx2")
@@ -241,52 +245,61 @@ cormatrix_to_excel <- function(data,
   wb$add_worksheet("p_values")$add_data(x = p_val)
 
   # create conditional formatting for the stars (as well as colours as we have no)
-  # one star
   # Compute the cell range for styling
   dims_fmt <- openxlsx2::wb_dims(cols = all.columns, rows = all.columns)
+
+  # gray diagonal (most specific, must be first to win for r = 1)
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 <= .2, r_values!B2 > 0, p_values!B2 < .05)",
-    style = "one_star_pink"
+    rule = "r_values!B2 = 1",
+    style = "gray_style"
   )
+
+  # three stars (p < .001) - most specific color ranges first
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 >= .2, p_values!B2 < .05)",
-    style = "one_star_peach"
+    rule = "AND(r_values!B2 >= .4, p_values!B2 < .001)",
+    style = "three_stars_red"
   )
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 >= .4, p_values!B2 < .05)",
-    style = "one_star_red"
+    rule = "AND(r_values!B2 >= .2, p_values!B2 < .001)",
+    style = "three_stars_peach"
   )
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 >= -.2, r_values!B2 < 0, p_values!B2 < .05)",
-    style = "one_star_lightblue"
+    rule = "AND(r_values!B2 <= .2, r_values!B2 > 0, p_values!B2 < .001)",
+    style = "three_stars_pink"
   )
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 <= -.2, p_values!B2 < .05)",
-    style = "one_star_midblue"
+    rule = "AND(r_values!B2 <= -.4, p_values!B2 < .001)",
+    style = "three_stars_darkblue"
   )
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 <= -.4, p_values!B2 < .05)",
-    style = "one_star_darkblue"
+    rule = "AND(r_values!B2 <= -.2, p_values!B2 < .001)",
+    style = "three_stars_midblue"
+  )
+  wb$add_conditional_formatting(
+    "r_values",
+    dims = dims_fmt,
+    rule = "AND(r_values!B2 >= -.2, r_values!B2 < 0, p_values!B2 < .001)",
+    style = "three_stars_lightblue"
   )
 
-  # two stars
+  # two stars (p < .01) - most specific color ranges first
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 <= .2, r_values!B2 > 0, p_values!B2 < .01)",
-    style = "two_stars_pink"
+    rule = "AND(r_values!B2 >= .4, p_values!B2 < .01)",
+    style = "two_stars_red"
   )
   wb$add_conditional_formatting(
     "r_values",
@@ -297,14 +310,14 @@ cormatrix_to_excel <- function(data,
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 >= .4, p_values!B2 < .01)",
-    style = "two_stars_red"
+    rule = "AND(r_values!B2 <= .2, r_values!B2 > 0, p_values!B2 < .01)",
+    style = "two_stars_pink"
   )
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 >= -.02, r_values!B2 < 0, p_values!B2 < .01)",
-    style = "two_stars_lightblue"
+    rule = "AND(r_values!B2 <= -.4, p_values!B2 < .01)",
+    style = "two_stars_darkblue"
   )
   wb$add_conditional_formatting(
     "r_values",
@@ -315,55 +328,49 @@ cormatrix_to_excel <- function(data,
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 <= -.4, p_values!B2 < .01)",
-    style = "two_stars_darkblue"
+    rule = "AND(r_values!B2 >= -.2, r_values!B2 < 0, p_values!B2 < .01)",
+    style = "two_stars_lightblue"
   )
 
-  # three stars
+  # one star (p < .05) - most specific color ranges first
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 <= .2, r_values!B2 > 0, p_values!B2 < .001)",
-    style = "three_stars_pink"
+    rule = "AND(r_values!B2 >= .4, p_values!B2 < .05)",
+    style = "one_star_red"
   )
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 >= .2, p_values!B2 < .001)",
-    style = "three_stars_peach"
+    rule = "AND(r_values!B2 >= .2, p_values!B2 < .05)",
+    style = "one_star_peach"
   )
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 >= .4, p_values!B2 < .001)",
-    style = "three_stars_red"
+    rule = "AND(r_values!B2 <= .2, r_values!B2 > 0, p_values!B2 < .05)",
+    style = "one_star_pink"
   )
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 >= -.2, r_values!B2 < 0, p_values!B2 < .001)",
-    style = "three_stars_lightblue"
+    rule = "AND(r_values!B2 <= -.4, p_values!B2 < .05)",
+    style = "one_star_darkblue"
   )
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 <= -.2, p_values!B2 < .001)",
-    style = "three_stars_midblue"
+    rule = "AND(r_values!B2 <= -.2, p_values!B2 < .05)",
+    style = "one_star_midblue"
   )
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
-    rule = "AND(r_values!B2 <= -.4, p_values!B2 < .001)",
-    style = "three_stars_darkblue"
+    rule = "AND(r_values!B2 >= -.2, r_values!B2 < 0, p_values!B2 < .05)",
+    style = "one_star_lightblue"
   )
 
-  # Other formatting
-  wb$add_conditional_formatting(
-    "r_values",
-    dims = dims_fmt,
-    rule = "AND(r_values!B2 = 1)",
-    style = "gray_style"
-  )
+  # no stars (for non-significant correlations)
   wb$add_conditional_formatting(
     "r_values",
     dims = dims_fmt,
@@ -371,18 +378,18 @@ cormatrix_to_excel <- function(data,
     style = "no_star"
   )
 
-  # p-values
+  # p-values (most specific first)
   wb$add_conditional_formatting(
     "p_values",
     dims = dims_fmt,
-    rule = "< 10",
-    style = "p_style"
+    rule = "== 0",
+    style = "gray_style"
   )
   wb$add_conditional_formatting(
     "p_values",
     dims = dims_fmt,
-    rule = "< .05",
-    style = "p_style1"
+    rule = "< .001",
+    style = "p_style3"
   )
   wb$add_conditional_formatting(
     "p_values",
@@ -393,14 +400,14 @@ cormatrix_to_excel <- function(data,
   wb$add_conditional_formatting(
     "p_values",
     dims = dims_fmt,
-    rule = "< .001",
-    style = "p_style3"
+    rule = "< .05",
+    style = "p_style1"
   )
   wb$add_conditional_formatting(
     "p_values",
     dims = dims_fmt,
-    rule = "== 0",
-    style = "gray_style"
+    rule = "< 10",
+    style = "p_style"
   )
 
   ## Freeze Panes
@@ -409,7 +416,8 @@ cormatrix_to_excel <- function(data,
 
   # Save Excel
   cat(paste0(
-    "\n\n [Correlation matrix '", filename,
+    "\n\n [Correlation matrix '",
+    filename,
     ".xlsx' has been saved to working directory (or where specified).]"
   ))
   openxlsx2::wb_save(wb, file = paste0(filename, ".xlsx"), overwrite = TRUE)
diff --git a/man/cor_smooth.Rd b/man/cor_smooth.Rd
index b2806a48..ddb3fa32 100644
--- a/man/cor_smooth.Rd
+++ b/man/cor_smooth.Rd
@@ -32,7 +32,7 @@ is done, inferential statistics (\emph{p}-values, confidence intervals, etc.) ar
 removed, as they are no longer valid.
 }
 \examples{
-\dontshow{if (requireNamespace("psych", quietly = TRUE)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (requireNamespace("psych", quietly = TRUE)) withAutoprint(\{ # examplesIf}
 set.seed(123)
 data <- as.matrix(mtcars)
 # Make missing data so pairwise correlation matrix is non-positive definite
diff --git a/man/cormatrix_to_excel.Rd b/man/cormatrix_to_excel.Rd
index ca5ae021..e140ffa6 100644
--- a/man/cormatrix_to_excel.Rd
+++ b/man/cormatrix_to_excel.Rd
@@ -33,7 +33,7 @@ correlation coefficients colour-coded based on effect size
 for small (.10), medium (.30), and large (.50) correlation sizes.
 }
 \examples{
-\dontshow{if (requireNamespace("openxlsx2", quietly = TRUE)) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (requireNamespace("openxlsx2", quietly = TRUE)) withAutoprint(\{ # examplesIf}
 \dontshow{
 .old_wd <- setwd(tempdir())
 }
diff --git a/man/correlation.Rd b/man/correlation.Rd
index 69dc1387..7852dbf9 100644
--- a/man/correlation.Rd
+++ b/man/correlation.Rd
@@ -272,7 +272,7 @@ Bayesian rank correlations (which have different priors).
 }
 }
 \examples{
-\dontshow{if (all(insight::check_if_installed(c("psych", "datawizard"), quietly = TRUE)) && getRversion() >= "4.1.0") (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (all(insight::check_if_installed(c("psych", "datawizard"), quietly = TRUE)) && getRversion() >= "4.1.0") withAutoprint(\{ # examplesIf}
 library(correlation)
 data(iris)
 
diff --git a/man/visualisation_recipe.easycormatrix.Rd b/man/visualisation_recipe.easycormatrix.Rd
index 453b1308..6ddf9ed4 100644
--- a/man/visualisation_recipe.easycormatrix.Rd
+++ b/man/visualisation_recipe.easycormatrix.Rd
@@ -61,7 +61,7 @@ the arguments described below.
 See examples \href{https://easystats.github.io/correlation/reference/visualisation_recipe.easycormatrix.html#ref-examples}{\strong{here}}.
 }
 \examples{
-\dontshow{if (require("see")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require("see")) withAutoprint(\{ # examplesIf}
 \donttest{
 rez <- cor_test(mtcars, "mpg", "wt")
 
@@ -77,7 +77,7 @@ plot(rez,
 )
 }
 \dontshow{\}) # examplesIf}
-\dontshow{if (require("see")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require("see")) withAutoprint(\{ # examplesIf}
 \donttest{
 rez <- correlation(mtcars)
 
@@ -106,7 +106,7 @@ layers <- visualisation_recipe(x,
 plot(layers) + theme_modern()
 }
 \dontshow{\}) # examplesIf}
-\dontshow{if (require("see") && require("tidygraph") && require("ggraph")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+\dontshow{if (require("see") && require("tidygraph") && require("ggraph")) withAutoprint(\{ # examplesIf}
 \donttest{
 rez <- correlation(iris)
 
diff --git a/tests/testthat/_snaps/renaming.md b/tests/testthat/_snaps/renaming.md
index 2fe9f676..9423b06a 100644
--- a/tests/testthat/_snaps/renaming.md
+++ b/tests/testthat/_snaps/renaming.md
@@ -5,9 +5,9 @@
     Output
       # Correlation Matrix (pearson-method)
       
-      Parameter1 | Parameter2 |    r |       95% CI | t(9) |         p
-      ----------------------------------------------------------------
-      x1         |         x2 | 1.00 | [1.00, 1.00] |  Inf | < .001***
+      Parameter1 | Parameter2 | r |       95% CI | t(9) |         p
+      -------------------------------------------------------------
+      x1         |         x2 | 1 | [1.00, 1.00] |  Inf | < .001***
       
       p-value adjustment method: Holm (1979)
       Observations: 11
@@ -19,9 +19,9 @@
     Output
       # Correlation Matrix (pearson-method)
       
-      Parameter1 | Parameter2 |    r |       95% CI | t(9) |         p
-      ----------------------------------------------------------------
-      var1       |       var2 | 1.00 | [1.00, 1.00] |  Inf | < .001***
+      Parameter1 | Parameter2 | r |       95% CI | t(9) |         p
+      -------------------------------------------------------------
+      var1       |       var2 | 1 | [1.00, 1.00] |  Inf | < .001***
       
       p-value adjustment method: Holm (1979)
       Observations: 11
diff --git a/tests/testthat/test-cor_test_na_present.R b/tests/testthat/test-cor_test_na_present.R
index 8449c265..1a17a3ac 100644
--- a/tests/testthat/test-cor_test_na_present.R
+++ b/tests/testthat/test-cor_test_na_present.R
@@ -11,7 +11,11 @@ test_that("cor_test kendall", {
   skip_if_not_or_load_if_installed("ggplot2")
 
   out <- cor_test(ggplot2::msleep, "brainwt", "sleep_rem", method = "kendall")
-  out2 <- suppressWarnings(stats::cor.test(ggplot2::msleep$brainwt, ggplot2::msleep$sleep_rem, method = "kendall"))
+  out2 <- suppressWarnings(stats::cor.test(
+    ggplot2::msleep$brainwt,
+    ggplot2::msleep$sleep_rem,
+    method = "kendall"
+  ))
 
   expect_equal(out$tau, out2$estimate[[1]], tolerance = 0.001)
   expect_equal(out$p, out2$p.value[[1]], tolerance = 0.001)
@@ -35,26 +39,58 @@ test_that("cor_test tetrachoric", {
   data$sleep_rem_binary <- as.numeric(data$sleep_rem > 1.2)
 
   # With Factors / Binary
-  expect_error(cor_test(data, "brainwt_binary", "sleep_rem_binary", method = "tetrachoric"))
+  expect_warning(expect_error(cor_test(
+    data,
+    "brainwt_binary",
+    "sleep_rem_binary",
+    method = "tetrachoric"
+  )))
 
   data$sleep_rem_ordinal <- as.factor(round(data$sleep_rem))
   data$brainwt_ordinal <- as.factor(round(data$brainwt))
 
-  out <- suppressWarnings(cor_test(data, "brainwt", "brainwt_ordinal", method = "polychoric"))
+  out <- suppressWarnings(cor_test(
+    data,
+    "brainwt",
+    "brainwt_ordinal",
+    method = "polychoric"
+  ))
   expect_equal(out$rho, 0.9999, tolerance = 0.01)
 
   # Biserial
-  expect_error(cor_test(data, "brainwt", "sleep_rem_binary", method = "pointbiserial"))
-
-  expect_error(cor_test(data, "brainwt", "sleep_rem_binary", method = "biserial"))
+  expect_error(cor_test(
+    data,
+    "brainwt",
+    "sleep_rem_binary",
+    method = "pointbiserial"
+  ))
+
+  expect_error(cor_test(
+    data,
+    "brainwt",
+    "sleep_rem_binary",
+    method = "biserial"
+  ))
 })
 
 
 test_that("cor_test robust", {
   skip_if_not_or_load_if_installed("ggplot2")
 
-  out1 <- cor_test(ggplot2::msleep, "brainwt", "sleep_rem", method = "pearson", ranktransform = TRUE)
-  out2 <- cor_test(ggplot2::msleep, "brainwt", "sleep_rem", method = "spearman", ranktransform = FALSE)
+  out1 <- cor_test(
+    ggplot2::msleep,
+    "brainwt",
+    "sleep_rem",
+    method = "pearson",
+    ranktransform = TRUE
+  )
+  out2 <- cor_test(
+    ggplot2::msleep,
+    "brainwt",
+    "sleep_rem",
+    method = "spearman",
+    ranktransform = FALSE
+  )
   expect_equal(out1$r, out2$rho, tolerance = 0.01)
 })
 
@@ -75,7 +111,12 @@ test_that("cor_test percentage", {
   skip_if_not_or_load_if_installed("ggplot2")
   skip_if_not_or_load_if_installed("WRS2")
 
-  out <- cor_test(ggplot2::msleep, "brainwt", "sleep_rem", method = "percentage")
+  out <- cor_test(
+    ggplot2::msleep,
+    "brainwt",
+    "sleep_rem",
+    method = "percentage"
+  )
   comparison <- WRS2::pbcor(ggplot2::msleep$brainwt, ggplot2::msleep$sleep_rem)
   expect_equal(out$r, as.numeric(comparison$cor), tolerance = 0.01)
 })
@@ -85,7 +126,12 @@ test_that("cor_test shepherd", {
   skip_if_not_or_load_if_installed("ggplot2")
 
   set.seed(333)
-  expect_error(cor_test(ggplot2::msleep, "brainwt", "sleep_rem", method = "shepherd"))
+  expect_error(cor_test(
+    ggplot2::msleep,
+    "brainwt",
+    "sleep_rem",
+    method = "shepherd"
+  ))
 })
 
 
@@ -121,19 +167,33 @@ test_that("cor_test gaussian", {
   expect_equal(out$r, -0.3679795, tolerance = 0.01)
 
   skip_if_not_or_load_if_installed("BayesFactor")
-  out <- cor_test(ggplot2::msleep, "brainwt", "sleep_rem", method = "gaussian", bayesian = TRUE)
+  out <- cor_test(
+    ggplot2::msleep,
+    "brainwt",
+    "sleep_rem",
+    method = "gaussian",
+    bayesian = TRUE
+  )
   expect_equal(out$rho, -0.3269572, tolerance = 0.01)
 })
 
 
 # Additional arguments ----------------------------------------------------
 
-
 test_that("cor_test one-sided p value", {
   skip_if_not_or_load_if_installed("ggplot2")
 
-  baseline <- cor.test(ggplot2::msleep$brainwt, ggplot2::msleep$sleep_rem, alternative = "greater")
-
-  out <- cor_test(ggplot2::msleep, "brainwt", "sleep_rem", alternative = "greater")
+  baseline <- cor.test(
+    ggplot2::msleep$brainwt,
+    ggplot2::msleep$sleep_rem,
+    alternative = "greater"
+  )
+
+  out <- cor_test(
+    ggplot2::msleep,
+    "brainwt",
+    "sleep_rem",
+    alternative = "greater"
+  )
   expect_equal(out$p, baseline$p.value, tolerance = 0.000001)
 })