From 8bfbf8df0b15e255e457086f2bc423398ef3dad7 Mon Sep 17 00:00:00 2001
From: Daniel <mail@danielluedecke.de>
Date: Sun, 26 May 2024 18:31:41 +0200
Subject: [PATCH 1/5] test on devs

---
 DESCRIPTION                 |  4 ++--
 R/methods.easycorrelation.R | 12 ++++++------
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 788ff0eb..9f5d33e2 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: correlation
 Title: Methods for Correlation Analysis
-Version: 0.8.4.2
+Version: 0.8.4.3
 Authors@R: 
     c(person(given = "Dominique",
              family = "Makowski",
@@ -95,4 +95,4 @@ Config/Needs/website:
     rstudio/bslib,
     r-lib/pkgdown,
     easystats/easystatstemplate
-Remotes: easystats/insight
+Remotes: easystats/insight, easystats/datawizard, easystats/parameters, easystats/bayestestR
diff --git a/R/methods.easycorrelation.R b/R/methods.easycorrelation.R
index 1b06136b..22c2f17c 100644
--- a/R/methods.easycorrelation.R
+++ b/R/methods.easycorrelation.R
@@ -11,7 +11,7 @@ summary.easycorrelation <- function(object,
     redundant <- FALSE
   }
 
-  frame <- .get_matrix(object, square = redundant)
+  cormatrix <- .get_matrix(object, square = redundant)
 
   # Add redundant
   if (redundant) {
@@ -30,11 +30,11 @@ summary.easycorrelation <- function(object,
     }
   }
 
-  out <- .create_matrix(frame, object, column = target, redundant = redundant)
+  out <- .create_matrix(cormatrix, object, column = target, redundant = redundant)
 
   # Fill attributes
   for (i in names(object)[!names(object) %in% c("Group", "Parameter1", "Parameter2", target)]) {
-    attri <- .create_matrix(frame, object, column = i, redundant = redundant)
+    attri <- .create_matrix(cormatrix, object, column = i, redundant = redundant)
     attr(out, i) <- attri
   }
 
@@ -120,7 +120,7 @@ as.list.easycorrelation <- function(x, cols = NULL, redundant = FALSE, ...) {
 #' @export
 standardize_names.easycorrelation <- function(data, ...) {
   ori <- data
-  names(data)[names(data) == datawizard::data_find(data, select = "(rho|tau)", regex = TRUE, verbose = FALSE)] <- "r"
+  names(data)[names(data) == datawizard::extract_column_names(data, select = "(rho|tau)", regex = TRUE, verbose = FALSE)] <- "r"
   data <- insight::standardize_names(as.data.frame(data), ...)
   class(data) <- class(ori)
   data
@@ -134,8 +134,8 @@ standardize_names.easycorrelation <- function(data, ...) {
   if ("Group" %in% names(object)) {
     out <- data.frame()
     for (g in unique(object$Group)) {
-      data <- object[object$Group == g, ]
-      m <- .fill_matrix(frame, data, column = column, redundant = redundant)
+      my_data <- object[object$Group == g, ]
+      m <- .fill_matrix(frame, my_data, column = column, redundant = redundant)
       m$Group <- g
       out <- rbind(out, m)
     }

From 8e9499555af9b8fc6219ae31512868fdc30f95c7 Mon Sep 17 00:00:00 2001
From: Daniel <mail@danielluedecke.de>
Date: Sun, 26 May 2024 20:41:00 +0200
Subject: [PATCH 2/5] lintr

---
 R/cor_test.R | 64 +++++++++++++++++++++++++---------------------------
 1 file changed, 31 insertions(+), 33 deletions(-)

diff --git a/R/cor_test.R b/R/cor_test.R
index cf1fa9d4..ccc83a6f 100644
--- a/R/cor_test.R
+++ b/R/cor_test.R
@@ -234,40 +234,38 @@ cor_test <- function(data,
     }
 
     # Bayesian
+  } else if (method %in% c("tetra", "tetrachoric")) {
+    insight::format_error("Tetrachoric Bayesian correlations are not supported yet. Get in touch if you want to contribute.")
+  } else if (method %in% c("poly", "polychoric")) {
+    insight::format_error("Polychoric Bayesian correlations are not supported yet. Get in touch if you want to contribute.")
+  } else if (method %in% c("biserial", "pointbiserial", "point-biserial")) {
+    insight::format_error("Biserial Bayesian correlations are not supported yet. Get in touch if you want to contribute.")
+  } else if (method == "biweight") {
+    insight::format_error("Biweight Bayesian correlations are not supported yet. Get in touch if you want to contribute.")
+  } else if (method == "distance") {
+    insight::format_error("Bayesian distance correlations are not supported yet. Get in touch if you want to contribute.")
+  } else if (method %in% c("percentage", "percentage_bend", "percentagebend", "pb")) {
+    insight::format_error("Bayesian Percentage Bend correlations are not supported yet. Get in touch if you want to contribute.")
+  } else if (method %in% c("blomqvist", "median", "medial")) {
+    insight::format_error("Bayesian Blomqvist correlations are not supported yet. Check-out the BBcor package (https://github.com/donaldRwilliams/BBcor).")
+  } else if (method == "hoeffding") {
+    insight::format_error("Bayesian Hoeffding's correlations are not supported yet. Check-out the BBcor package (https://github.com/donaldRwilliams/BBcor).")
+  } else if (method == "gamma") {
+    insight::format_error("Bayesian gamma correlations are not supported yet. Get in touch if you want to contribute.")
+  } else if (method %in% c("shepherd", "sheperd", "shepherdspi", "pi")) {
+    out <- .cor_test_shepherd(data, x, y, ci = ci, bayesian = TRUE, ...)
   } else {
-    if (method %in% c("tetra", "tetrachoric")) {
-      insight::format_error("Tetrachoric Bayesian correlations are not supported yet. Get in touch if you want to contribute.")
-    } else if (method %in% c("poly", "polychoric")) {
-      insight::format_error("Polychoric Bayesian correlations are not supported yet. Get in touch if you want to contribute.")
-    } else if (method %in% c("biserial", "pointbiserial", "point-biserial")) {
-      insight::format_error("Biserial Bayesian correlations are not supported yet. Get in touch if you want to contribute.")
-    } else if (method == "biweight") {
-      insight::format_error("Biweight Bayesian correlations are not supported yet. Get in touch if you want to contribute.")
-    } else if (method == "distance") {
-      insight::format_error("Bayesian distance correlations are not supported yet. Get in touch if you want to contribute.")
-    } else if (method %in% c("percentage", "percentage_bend", "percentagebend", "pb")) {
-      insight::format_error("Bayesian Percentage Bend correlations are not supported yet. Get in touch if you want to contribute.")
-    } else if (method %in% c("blomqvist", "median", "medial")) {
-      insight::format_error("Bayesian Blomqvist correlations are not supported yet. Check-out the BBcor package (https://github.com/donaldRwilliams/BBcor).")
-    } else if (method == "hoeffding") {
-      insight::format_error("Bayesian Hoeffding's correlations are not supported yet. Check-out the BBcor package (https://github.com/donaldRwilliams/BBcor).")
-    } else if (method == "gamma") {
-      insight::format_error("Bayesian gamma correlations are not supported yet. Get in touch if you want to contribute.")
-    } else if (method %in% c("shepherd", "sheperd", "shepherdspi", "pi")) {
-      out <- .cor_test_shepherd(data, x, y, ci = ci, bayesian = TRUE, ...)
-    } else {
-      out <- .cor_test_bayes(
-        data,
-        x,
-        y,
-        ci = ci,
-        method = method,
-        bayesian_prior = bayesian_prior,
-        bayesian_ci_method = bayesian_ci_method,
-        bayesian_test = bayesian_test,
-        ...
-      )
-    }
+    out <- .cor_test_bayes(
+      data,
+      x,
+      y,
+      ci = ci,
+      method = method,
+      bayesian_prior = bayesian_prior,
+      bayesian_ci_method = bayesian_ci_method,
+      bayesian_test = bayesian_test,
+      ...
+    )
   }
 
   # Replace by NANs if invalid

From c86e88ea3f2ebd152c75d86dea4ea7b270feff7b Mon Sep 17 00:00:00 2001
From: Daniel <mail@danielluedecke.de>
Date: Sun, 26 May 2024 20:41:55 +0200
Subject: [PATCH 3/5] lintr

---
 R/cor_test.R | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/R/cor_test.R b/R/cor_test.R
index ccc83a6f..481dc782 100644
--- a/R/cor_test.R
+++ b/R/cor_test.R
@@ -282,8 +282,11 @@ cor_test <- function(data,
 
   # Reorder columns
   if ("CI_low" %in% names(out)) {
-    order <- c("Parameter1", "Parameter2", "r", "rho", "tau", "Dxy", "CI", "CI_low", "CI_high")
-    out <- out[c(order[order %in% names(out)], setdiff(colnames(out), order[order %in% names(out)]))]
+    col_order <- c("Parameter1", "Parameter2", "r", "rho", "tau", "Dxy", "CI", "CI_low", "CI_high")
+    out <- out[c(
+      col_order[col_order %in% names(out)],
+      setdiff(colnames(out), col_order[col_order %in% names(out)])
+    )]
   }
 
   # Output

From 6fef4508c8a4fa3765ad86e3f4fb5f132ba4d098 Mon Sep 17 00:00:00 2001
From: Daniel <mail@danielluedecke.de>
Date: Sun, 26 May 2024 21:00:20 +0200
Subject: [PATCH 4/5] lintr, docs

---
 R/cor_sort.R                              | 16 ++--
 R/cor_test.R                              |  4 +-
 R/cor_test_bayes.R                        |  2 +-
 R/cor_test_biserial.R                     |  8 +-
 R/cor_test_distance.R                     | 42 +++++------
 R/cor_test_freq.R                         |  6 +-
 R/cor_text.R                              | 34 ++++-----
 R/cor_to_cov.R                            | 10 +--
 R/cor_to_pcor.R                           | 55 +++++++-------
 R/cormatrix_to_excel.R                    | 16 ++--
 R/correlation.R                           | 91 +++++++++++------------
 R/methods_format.R                        | 14 ++--
 inst/WORDLIST                             |  1 +
 man/cor_test.Rd                           |  4 +-
 tests/testthat/test-cor_test_na_present.R |  8 +-
 15 files changed, 156 insertions(+), 155 deletions(-)

diff --git a/R/cor_sort.R b/R/cor_sort.R
index c761ceaa..7c30d22f 100644
--- a/R/cor_sort.R
+++ b/R/cor_sort.R
@@ -26,9 +26,9 @@ cor_sort <- function(x, distance = "correlation", hclust_method = "complete", ..
 
 #' @export
 cor_sort.easycorrelation <- function(x, distance = "correlation", hclust_method = "complete", ...) {
-  order <- .cor_sort_order(as.matrix(x), distance = distance, hclust_method = hclust_method, ...)
-  x$Parameter1 <- factor(x$Parameter1, levels = order)
-  x$Parameter2 <- factor(x$Parameter2, levels = order)
+  col_order <- .cor_sort_order(as.matrix(x), distance = distance, hclust_method = hclust_method, ...)
+  x$Parameter1 <- factor(x$Parameter1, levels = col_order)
+  x$Parameter2 <- factor(x$Parameter2, levels = col_order)
   reordered <- x[order(x$Parameter1, x$Parameter2), ]
 
   # Restore class and attributes
@@ -55,11 +55,11 @@ cor_sort.easycormatrix <- function(x, distance = "correlation", hclust_method =
   m <- x
   row.names(m) <- x$Parameter
   m <- as.matrix(m[names(m)[names(m) != "Parameter"]])
-  order <- .cor_sort_order(m, distance = distance, hclust_method = hclust_method, ...)
+  col_order <- .cor_sort_order(m, distance = distance, hclust_method = hclust_method, ...)
 
   # Reorder
-  x$Parameter <- factor(x$Parameter, levels = order)
-  reordered <- x[order(x$Parameter), c("Parameter", order)]
+  x$Parameter <- factor(x$Parameter, levels = col_order)
+  reordered <- x[order(x$Parameter), c("Parameter", col_order)]
 
   # Restore class and attributes
   attributes(reordered) <- utils::modifyList(
@@ -76,8 +76,8 @@ cor_sort.easycormatrix <- function(x, distance = "correlation", hclust_method =
 
 #' @export
 cor_sort.matrix <- function(x, distance = "correlation", hclust_method = "complete", ...) {
-  order <- .cor_sort_order(x, distance = distance, hclust_method = hclust_method, ...)
-  reordered <- x[order, order]
+  col_order <- .cor_sort_order(x, distance = distance, hclust_method = hclust_method, ...)
+  reordered <- x[col_order, col_order]
 
   # Restore class and attributes
   attributes(reordered) <- utils::modifyList(
diff --git a/R/cor_test.R b/R/cor_test.R
index 481dc782..60d31cdc 100644
--- a/R/cor_test.R
+++ b/R/cor_test.R
@@ -112,7 +112,9 @@
 #'
 #' # Partial
 #' cor_test(iris, "Sepal.Length", "Sepal.Width", partial = TRUE)
-#' cor_test(iris, "Sepal.Length", "Sepal.Width", multilevel = TRUE)
+#' if (require("lme4", quietly = TRUE)) {
+#'   cor_test(iris, "Sepal.Length", "Sepal.Width", multilevel = TRUE)
+#' }
 #' cor_test(iris, "Sepal.Length", "Sepal.Width", partial_bayesian = TRUE)
 #' }
 #' @export
diff --git a/R/cor_test_bayes.R b/R/cor_test_bayes.R
index 288b5a2c..d3519b25 100644
--- a/R/cor_test_bayes.R
+++ b/R/cor_test_bayes.R
@@ -17,7 +17,7 @@
     var_x <- datawizard::ranktransform(var_x, sign = TRUE, method = "average")
     var_y <- datawizard::ranktransform(var_y, sign = TRUE, method = "average")
     method <- "Bayesian Spearman"
-  } else if (tolower(method) %in% "gaussian") {
+  } else if (tolower(method) == "gaussian") {
     var_x <- stats::qnorm(rank(var_x) / (length(var_x) + 1))
     var_y <- stats::qnorm(rank(var_y) / (length(var_y) + 1))
     method <- "Bayesian Gaussian rank"
diff --git a/R/cor_test_biserial.R b/R/cor_test_biserial.R
index f6aea4d4..99ecda53 100644
--- a/R/cor_test_biserial.R
+++ b/R/cor_test_biserial.R
@@ -56,11 +56,11 @@
 
   m1 <- mean(var_x[var_y == 1])
   m0 <- mean(var_x[var_y == 0])
-  q <- mean(var_y)
-  p <- 1 - q
-  zp <- stats::dnorm(stats::qnorm(q))
+  quan <- mean(var_y)
+  p <- 1 - quan
+  zp <- stats::dnorm(stats::qnorm(quan))
 
-  r <- (((m1 - m0) * (p * q / zp)) / stats::sd(var_x))
+  r <- (((m1 - m0) * (p * quan / zp)) / stats::sd(var_x))
 
   p <- cor_to_p(r, n = length(var_x))
   ci_vals <- cor_to_ci(r, n = length(var_x), ci = ci)
diff --git a/R/cor_test_distance.R b/R/cor_test_distance.R
index 2eb1c863..da35cb8a 100644
--- a/R/cor_test_distance.R
+++ b/R/cor_test_distance.R
@@ -3,21 +3,7 @@
   var_x <- .complete_variable_x(data, x, y)
   var_y <- .complete_variable_y(data, x, y)
 
-  if (!corrected) {
-    rez <- .cor_test_distance_raw(var_x, var_y, index = 1)
-    rez <- data.frame(
-      Parameter1 = x,
-      Parameter2 = y,
-      r = rez$r,
-      CI_low = NA,
-      CI_high = NA,
-      t = NA,
-      df_error = NA,
-      p = NA,
-      Method = "Distance",
-      stringsAsFactors = FALSE
-    )
-  } else {
+  if (corrected) {
     rez <- .cor_test_distance_corrected(var_x, var_y, ci = ci)
     rez <- data.frame(
       Parameter1 = x,
@@ -31,6 +17,20 @@
       Method = "Distance (Bias Corrected)",
       stringsAsFactors = FALSE
     )
+  } else {
+    rez <- .cor_test_distance_raw(var_x, var_y, index = 1)
+    rez <- data.frame(
+      Parameter1 = x,
+      Parameter2 = y,
+      r = rez$r,
+      CI_low = NA,
+      CI_high = NA,
+      t = NA,
+      df_error = NA,
+      p = NA,
+      Method = "Distance",
+      stringsAsFactors = FALSE
+    )
   }
 
   rez
@@ -60,14 +60,14 @@
   M <- n * (n - 3) / 2
   dof <- M - 1
 
-  t <- sqrt(M - 1) * r / sqrt(1 - r^2)
-  p <- 1 - stats::pt(t, df = dof)
+  tstat <- sqrt(M - 1) * r / sqrt(1 - r^2)
+  p <- 1 - stats::pt(tstat, df = dof)
 
   ci_vals <- cor_to_ci(r, n = n, ci = ci)
 
   list(
     r = r,
-    t = t,
+    t = tstat,
     df_error = dof,
     p = p,
     CI_low = ci_vals$CI_low,
@@ -91,16 +91,16 @@
   A <- .A_kl(x, index)
   B <- .A_kl(y, index)
 
-  cov <- sqrt(mean(A * B))
+  cov_ab <- sqrt(mean(A * B))
   dVarX <- sqrt(mean(A * A))
   dVarY <- sqrt(mean(B * B))
   V <- sqrt(dVarX * dVarY)
   if (V > 0) {
-    r <- cov / V
+    r <- cov_ab / V
   } else {
     r <- 0
   }
-  list(r = r, cov = cov)
+  list(r = r, cov = cov_ab)
 }
 
 
diff --git a/R/cor_test_freq.R b/R/cor_test_freq.R
index 0d43056f..7ea4d175 100644
--- a/R/cor_test_freq.R
+++ b/R/cor_test_freq.R
@@ -42,10 +42,10 @@
 
 
 .extract_corr_parameters <- function(model) {
-  names <- unlist(strsplit(model$data.name, " and ", fixed = TRUE))
+  data_names <- unlist(strsplit(model$data.name, " and ", fixed = TRUE))
   out <- data.frame(
-    "Parameter1" = names[1],
-    "Parameter2" = names[2],
+    Parameter1 = data_names[1],
+    Parameter2 = data_names[2],
     stringsAsFactors = FALSE
   )
 
diff --git a/R/cor_text.R b/R/cor_text.R
index 481dc118..fa3d0ded 100644
--- a/R/cor_text.R
+++ b/R/cor_text.R
@@ -20,28 +20,28 @@ cor_text <- function(x, show_ci = TRUE, show_statistic = TRUE, show_sig = TRUE,
   # Estimate
   candidates <- c("rho", "r", "tau", "Difference", "r_rank_biserial")
   estimate <- candidates[candidates %in% names(x)][1]
-  text <- paste0(tolower(estimate), " = ", insight::format_value(x[[estimate]]))
+  out_text <- paste0(tolower(estimate), " = ", insight::format_value(x[[estimate]]))
 
   # CI
   if (show_ci && all(c("CI_high", "CI_low") %in% names(x))) {
     if (!is.null(attributes(x$conf.int)$conf.level)) {
       # htest
-      text <- paste0(
-        text,
+      out_text <- paste0(
+        out_text,
         ", ",
         insight::format_ci(x$CI_low, x$CI_high, ci = attributes(x$conf.int)$conf.level)
       )
     } else if ("CI" %in% names(x)) {
       # param
-      text <- paste0(
-        text,
+      out_text <- paste0(
+        out_text,
         ", ",
         insight::format_ci(x$CI_low, x$CI_high, ci = x$CI)
       )
     } else if ("ci" %in% names(attributes(x))) {
       # param
-      text <- paste0(
-        text,
+      out_text <- paste0(
+        out_text,
         ", ",
         insight::format_ci(x$CI_low, x$CI_high, ci = attributes(x)$ci)
       )
@@ -51,36 +51,36 @@ cor_text <- function(x, show_ci = TRUE, show_statistic = TRUE, show_sig = TRUE,
   # Statistic
   if (show_statistic) {
     if ("t" %in% names(x)) {
-      text <- paste0(
-        text,
+      out_text <- paste0(
+        out_text,
         ", t(",
         insight::format_value(x$df, protect_integers = TRUE),
         ") = ",
         insight::format_value(x$t)
       )
     } else if ("S" %in% names(x)) {
-      text <- paste0(text, ", S = ", insight::format_value(x$S))
+      out_text <- paste0(out_text, ", S = ", insight::format_value(x$S))
     } else if ("z" %in% names(x)) {
-      text <- paste0(text, ", z = ", insight::format_value(table$z))
+      out_text <- paste0(out_text, ", z = ", insight::format_value(table$z))
     } else if ("W" %in% names(x)) {
-      text <- paste0("W = ", insight::format_value(x$W))
+      out_text <- paste0("W = ", insight::format_value(x$W))
     } else if ("Chi2" %in% names(x)) {
-      text <- paste0(text, ", Chi2 = ", insight::format_value(x$Chi2))
+      out_text <- paste0(out_text, ", Chi2 = ", insight::format_value(x$Chi2))
     }
   }
 
   # Significance
   if (show_sig) {
     if ("p" %in% names(x)) {
-      text <- paste0(text, ", ", insight::format_p(x$p, digits = "apa", ...))
+      out_text <- paste0(out_text, ", ", insight::format_p(x$p, digits = "apa", ...))
     } else if ("BF" %in% names(x)) {
       exact <- match.call()[["exact"]]
       if (is.null(exact)) exact <- TRUE
-      text <- paste0(text, ", ", insight::format_bf(x$BF, exact = exact, ...))
+      out_text <- paste0(out_text, ", ", insight::format_bf(x$BF, exact = exact, ...))
     } else if ("pd" %in% names(x)) {
-      text <- paste0(text, ", ", insight::format_pd(x$pd, ...))
+      out_text <- paste0(out_text, ", ", insight::format_pd(x$pd, ...))
     }
   }
 
-  text
+  out_text
 }
diff --git a/R/cor_to_cov.R b/R/cor_to_cov.R
index f876c9c6..9ba75ff7 100644
--- a/R/cor_to_cov.R
+++ b/R/cor_to_cov.R
@@ -43,8 +43,8 @@ cor_to_cov <- function(cor, sd = NULL, variance = NULL, tol = .Machine$double.ep
     is_symmetric <- FALSE
   }
   p <- dim(cor)[1]
-  q <- p * (p - 1) / 2
-  if (isTRUE(all.equal(cor[lower.tri(cor)], rep(0, q))) || isTRUE(all.equal(cor[upper.tri(cor)], rep(0, q)))) {
+  quan <- p * (p - 1) / 2
+  if (isTRUE(all.equal(cor[lower.tri(cor)], rep(0, quan))) || isTRUE(all.equal(cor[upper.tri(cor)], rep(0, quan)))) {
     is_triangular <- TRUE
   } else {
     is_triangular <- FALSE
@@ -53,7 +53,7 @@ cor_to_cov <- function(cor, sd = NULL, variance = NULL, tol = .Machine$double.ep
     insight::format_error("'cor' should be either a symmetric or a triangular matrix")
   }
 
-  cov <- diag(sd) %*% cor %*% diag(sd)
-  colnames(cov) <- rownames(cov) <- colnames(cor)
-  cov
+  cov_matrix <- diag(sd) %*% cor %*% diag(sd)
+  colnames(cov_matrix) <- rownames(cov_matrix) <- colnames(cor)
+  cov_matrix
 }
diff --git a/R/cor_to_pcor.R b/R/cor_to_pcor.R
index b0bc1512..1837b980 100644
--- a/R/cor_to_pcor.R
+++ b/R/cor_to_pcor.R
@@ -52,10 +52,10 @@ cor_to_pcor.matrix <- function(cor, tol = .Machine$double.eps^(2 / 3)) {
 
 #' @export
 cor_to_pcor.easycormatrix <- function(cor, tol = .Machine$double.eps^(2 / 3)) {
-  if (!inherits(cor, "matrix")) {
-    .cor_to_pcor_easycormatrix(cor = cor, tol = tol)
-  } else {
+  if (inherits(cor, "matrix")) {
     NextMethod()
+  } else {
+    .cor_to_pcor_easycormatrix(cor = cor, tol = tol)
   }
 }
 
@@ -86,10 +86,10 @@ pcor_to_cor.matrix <- function(pcor, tol = .Machine$double.eps^(2 / 3)) {
 
 #' @export
 pcor_to_cor.easycormatrix <- function(pcor, tol = .Machine$double.eps^(2 / 3)) {
-  if (!inherits(pcor, "matrix")) {
-    .cor_to_pcor_easycormatrix(pcor = pcor, tol = tol)
-  } else {
+  if (inherits(pcor, "matrix")) {
     NextMethod()
+  } else {
+    .cor_to_pcor_easycormatrix(pcor = pcor, tol = tol)
   }
 }
 
@@ -114,28 +114,28 @@ pcor_to_cor.easycorrelation <- function(pcor, tol = .Machine$double.eps^(2 / 3))
 
   # Extract info
   p_adjust <- attributes(cor)$p_adjust
-  nobs <- as.matrix(attributes(summary(cor, redundant = TRUE))$n_Obs[-1])
+  number_obs <- as.matrix(attributes(summary(cor, redundant = TRUE))$n_Obs[-1])
 
   # Get Statistics
-  p <- cor_to_p(r, n = nobs, method = "pearson")
-  ci_vals <- cor_to_ci(r, n = nobs, ci = attributes(cor)$ci)
+  p <- cor_to_p(r, n = number_obs, method = "pearson")
+  ci_vals <- cor_to_ci(r, n = number_obs, ci = attributes(cor)$ci)
 
   # Replace
   newdata <- data.frame()
   for (i in seq_len(nrow(cor))) {
-    row <- row.names(r) == cor[i, "Parameter1"]
-    col <- colnames(r) == cor[i, "Parameter2"]
+    row_index <- row.names(r) == cor[i, "Parameter1"]
+    col_index <- colnames(r) == cor[i, "Parameter2"]
     newdata <- rbind(
       newdata,
       data.frame(
-        r = r[row, col],
-        CI_low = ci_vals$CI_low[row, col],
-        CI_high = ci_vals$CI_high[row, col],
-        t = p$statistic[row, col],
-        df_error = nobs[row, col] - 2,
-        p = p$p[row, col],
+        r = r[row_index, col_index],
+        CI_low = ci_vals$CI_low[row_index, col_index],
+        CI_high = ci_vals$CI_high[row_index, col_index],
+        t = p$statistic[row_index, col_index],
+        df_error = number_obs[row_index, col_index] - 2,
+        p = p$p[row_index, col_index],
         Method = "Pearson",
-        n_Obs = nobs[row, col],
+        n_Obs = number_obs[row_index, col_index],
         stringsAsFactors = FALSE
       )
     )
@@ -183,10 +183,10 @@ pcor_to_cor.easycorrelation <- function(pcor, tol = .Machine$double.eps^(2 / 3))
   }
 
   p_adjust <- attributes(cor)$p_adjust
-  nobs <- as.matrix(attributes(cor)$n_Obs[-1])
+  number_obs <- as.matrix(attributes(cor)$n_Obs[-1])
 
-  p <- cor_to_p(r, n = nobs, method = "pearson")
-  ci_vals <- cor_to_ci(r, n = nobs, ci = attributes(cor)$ci)
+  p <- cor_to_p(r, n = number_obs, method = "pearson")
+  ci_vals <- cor_to_ci(r, n = number_obs, ci = attributes(cor)$ci)
   r <- cbind(data.frame(Parameter = row.names(r)), r)
   row.names(r) <- NULL
 
@@ -247,15 +247,12 @@ pcor_to_cor.easycorrelation <- function(pcor, tol = .Machine$double.eps^(2 / 3))
   # Get Cormatrix
   if (is.null(cor)) {
     if (is.null(cov)) {
-      stop("A correlation or covariance matrix is required.", call. = FALSE)
-    } else {
-      cor <- stats::cov2cor(cov)
-    }
-  } else {
-    if (inherits(cor, "easycormatrix") && colnames(cor)[1] == "Parameter") {
-      row.names(cor) <- cor$Parameter
-      cor <- as.matrix(cor[-1])
+      insight::format_error("A correlation or covariance matrix is required.")
     }
+    cor <- stats::cov2cor(cov)
+  } else if (inherits(cor, "easycormatrix") && colnames(cor)[1] == "Parameter") {
+    row.names(cor) <- cor$Parameter
+    cor <- as.matrix(cor[-1])
   }
   cor
 }
diff --git a/R/cormatrix_to_excel.R b/R/cormatrix_to_excel.R
index a028ad56..700f4673 100644
--- a/R/cormatrix_to_excel.R
+++ b/R/cormatrix_to_excel.R
@@ -47,19 +47,19 @@ cormatrix_to_excel <- function(data,
                                print.mat = TRUE,
                                ...) {
   if (missing(filename)) {
-    stop("Argument 'filename' required (as per CRAN policies)")
+    insight::format_error("Argument 'filename' required (as per CRAN policies).")
   }
 
   insight::check_if_installed("openxlsx2")
 
   # create correlation matrix with p values
-  cm <- correlation::correlation(data, ...)
-  cm <- summary(cm, redundant = TRUE)
-  all.columns <- 2:(ncol(cm))
+  cormatrix <- correlation::correlation(data, ...)
+  cormatrix <- summary(cormatrix, redundant = TRUE)
+  all.columns <- 2:(ncol(cormatrix))
   if (isTRUE(print.mat)) {
-    print(cm)
+    print(cormatrix)
   }
-  pf <- attr(cm, "p")
+  p_val <- attr(cormatrix, "p")
 
   # Define colours
   style_gray <- c(rgb = "C1CDCD")
@@ -237,8 +237,8 @@ cormatrix_to_excel <- function(data,
   # wb$styles_mgr$dxf
 
   # create the worksheets and write the data to the worksheets.
-  wb$add_worksheet("r_values")$add_data(x = cm)
-  wb$add_worksheet("p_values")$add_data(x = pf)
+  wb$add_worksheet("r_values")$add_data(x = cormatrix)
+  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
diff --git a/R/correlation.R b/R/correlation.R
index 4297cefe..c450d6c9 100644
--- a/R/correlation.R
+++ b/R/correlation.R
@@ -369,19 +369,19 @@ correlation <- function(data,
   attributes(out) <- c(
     attributes(out),
     list(
-      "data" = data,
-      "data2" = data2,
-      "modelframe" = rez$data,
-      "ci" = ci,
-      "n" = nrow(data),
-      "method" = method,
-      "bayesian" = bayesian,
-      "p_adjust" = p_adjust,
-      "partial" = partial,
-      "multilevel" = multilevel,
-      "partial_bayesian" = partial_bayesian,
-      "bayesian_prior" = bayesian_prior,
-      "include_factors" = include_factors
+      data = data,
+      data2 = data2,
+      modelframe = rez$data,
+      ci = ci,
+      n = nrow(data),
+      method = method,
+      bayesian = bayesian,
+      p_adjust = p_adjust,
+      partial = partial,
+      multilevel = multilevel,
+      partial_bayesian = partial_bayesian,
+      bayesian_prior = bayesian_prior,
+      include_factors = include_factors
     )
   )
 
@@ -429,39 +429,38 @@ correlation <- function(data,
   if (!is.null(data2)) {
     if (inherits(data2, "grouped_df")) {
       groups2 <- setdiff(colnames(attributes(data2)$groups), ".rows")
-      if (all.equal(groups, groups2)) {
-        ungrouped_y <- as.data.frame(data2)
-        ylist <- split(ungrouped_y, ungrouped_y[groups], sep = " - ")
-        modelframe <- data.frame()
-        out <- data.frame()
-        for (i in names(xlist)) {
-          xlist[[i]][groups] <- NULL
-          ylist[[i]][groups] <- NULL
-          rez <- .correlation(
-            xlist[[i]],
-            data2 = ylist[[i]],
-            method = method,
-            p_adjust = p_adjust,
-            ci = ci,
-            bayesian = bayesian,
-            bayesian_prior = bayesian_prior,
-            bayesian_ci_method = bayesian_ci_method,
-            bayesian_test = bayesian_test,
-            redundant = redundant,
-            include_factors = include_factors,
-            partial = partial,
-            partial_bayesian = partial_bayesian,
-            multilevel = multilevel,
-            ranktransform = ranktransform,
-            winsorize = winsorize
-          )
-          modelframe_current <- rez$data
-          rez$params$Group <- modelframe_current$Group <- i
-          out <- rbind(out, rez$params)
-          modelframe <- rbind(modelframe, modelframe_current)
-        }
-      } else {
-        stop("'data2' should have the same grouping characteristics as data.", call. = FALSE)
+      if (!all.equal(groups, groups2)) {
+        insight::format_error("'data2' should have the same grouping characteristics as data.")
+      }
+      ungrouped_y <- as.data.frame(data2)
+      ylist <- split(ungrouped_y, ungrouped_y[groups], sep = " - ")
+      modelframe <- data.frame()
+      out <- data.frame()
+      for (i in names(xlist)) {
+        xlist[[i]][groups] <- NULL
+        ylist[[i]][groups] <- NULL
+        rez <- .correlation(
+          xlist[[i]],
+          data2 = ylist[[i]],
+          method = method,
+          p_adjust = p_adjust,
+          ci = ci,
+          bayesian = bayesian,
+          bayesian_prior = bayesian_prior,
+          bayesian_ci_method = bayesian_ci_method,
+          bayesian_test = bayesian_test,
+          redundant = redundant,
+          include_factors = include_factors,
+          partial = partial,
+          partial_bayesian = partial_bayesian,
+          multilevel = multilevel,
+          ranktransform = ranktransform,
+          winsorize = winsorize
+        )
+        modelframe_current <- rez$data
+        rez$params$Group <- modelframe_current$Group <- i
+        out <- rbind(out, rez$params)
+        modelframe <- rbind(modelframe, modelframe_current)
       }
     }
     # else
diff --git a/R/methods_format.R b/R/methods_format.R
index c30d910c..24300db7 100644
--- a/R/methods_format.R
+++ b/R/methods_format.R
@@ -45,7 +45,7 @@ format.easycormatrix <- function(x,
   # If it's a real matrix
   if (!"Parameter" %in% colnames(x)) {
     m <- as.data.frame(x)
-    return(cbind(data.frame("Variables" = row.names(x)), m))
+    return(cbind(data.frame(Variables = row.names(x)), m))
   }
 
   # Find attributes
@@ -105,7 +105,7 @@ format.easycormatrix <- function(x,
     }
 
     if (!stars_only) {
-      sig[, nums] <- sapply(sig[, nums], function(x) ifelse(x != "", paste0(" (", x, ")"), ""))
+      sig[, nums] <- sapply(sig[, nums], function(x) ifelse(x != "", paste0(" (", x, ")"), "")) # nolint
     }
 
     if (include_significance || stars) {
@@ -146,11 +146,11 @@ format.easycormatrix <- function(x,
   # N-obs
   if (!is.null(x$n_Obs)) {
     if (length(unique(x$n_Obs)) == 1) {
-      nobs <- unique(x$n_Obs)
+      number_obs <- unique(x$n_Obs)
     } else {
-      nobs <- paste0(min(x$n_Obs), "-", max(x$n_Obs))
+      number_obs <- paste0(min(x$n_Obs), "-", max(x$n_Obs))
     }
-    footer <- paste0(footer, "\nObservations: ", nobs)
+    footer <- paste0(footer, "\nObservations: ", number_obs)
   }
 
   # final new line
@@ -158,8 +158,8 @@ format.easycormatrix <- function(x,
 
   # for html/markdown, create list
   if (!is.null(format) && format != "text") {
-    footer <- unlist(strsplit(footer, "\n"))
-    footer <- as.list(footer[nchar(footer) > 0])
+    footer <- unlist(strsplit(footer, "\n", fixed = TRUE))
+    footer <- as.list(footer[nzchar(footer, keepNA = TRUE)])
   }
 
   footer
diff --git a/inst/WORDLIST b/inst/WORDLIST
index ad94ff56..101ffc38 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -94,6 +94,7 @@ pinv
 polychoric
 pracma
 rOpenSci
+rempsyc
 rescaled
 ressembles
 rmarkdown
diff --git a/man/cor_test.Rd b/man/cor_test.Rd
index faa3a768..a4e18f39 100644
--- a/man/cor_test.Rd
+++ b/man/cor_test.Rd
@@ -271,7 +271,9 @@ if (require("psych", quietly = TRUE) && require("rstanarm", quietly = TRUE)) {
 
 # Partial
 cor_test(iris, "Sepal.Length", "Sepal.Width", partial = TRUE)
-cor_test(iris, "Sepal.Length", "Sepal.Width", multilevel = TRUE)
+if (require("lme4", quietly = TRUE)) {
+  cor_test(iris, "Sepal.Length", "Sepal.Width", multilevel = TRUE)
+}
 cor_test(iris, "Sepal.Length", "Sepal.Width", partial_bayesian = TRUE)
 }
 }
diff --git a/tests/testthat/test-cor_test_na_present.R b/tests/testthat/test-cor_test_na_present.R
index 8e1b0c4e..5f8d6502 100644
--- a/tests/testthat/test-cor_test_na_present.R
+++ b/tests/testthat/test-cor_test_na_present.R
@@ -11,7 +11,7 @@ test_that("cor_test kendall", {
   skip_if_not_or_load_if_installed("ggplot2")
 
   out <- cor_test(ggplot2::msleep, "brainwt", "sleep_rem", method = "kendall")
-  out2 <- 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)
@@ -31,8 +31,8 @@ test_that("cor_test tetrachoric", {
   skip_if_not_or_load_if_installed("ggplot2")
 
   data <- ggplot2::msleep
-  data$brainwt_binary <- ifelse(data$brainwt > 3, 1, 0)
-  data$sleep_rem_binary <- ifelse(data$sleep_rem > 1.2, 1, 0)
+  data$brainwt_binary <- as.numeric(data$brainwt > 3)
+  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"))
@@ -40,7 +40,7 @@ test_that("cor_test tetrachoric", {
   data$sleep_rem_ordinal <- as.factor(round(data$sleep_rem))
   data$brainwt_ordinal <- as.factor(round(data$brainwt))
 
-  out <- 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

From 293880eee42ddd077a6251c2e236e4e99653a2bf Mon Sep 17 00:00:00 2001
From: Daniel <mail@danielluedecke.de>
Date: Sun, 26 May 2024 21:06:31 +0200
Subject: [PATCH 5/5] fix warnings

---
 R/cor_test.R                   | 4 +++-
 man/cor_test.Rd                | 4 +++-
 tests/testthat/test-cor_test.R | 8 ++++----
 3 files changed, 10 insertions(+), 6 deletions(-)

diff --git a/R/cor_test.R b/R/cor_test.R
index 60d31cdc..787caf23 100644
--- a/R/cor_test.R
+++ b/R/cor_test.R
@@ -115,7 +115,9 @@
 #' if (require("lme4", quietly = TRUE)) {
 #'   cor_test(iris, "Sepal.Length", "Sepal.Width", multilevel = TRUE)
 #' }
-#' cor_test(iris, "Sepal.Length", "Sepal.Width", partial_bayesian = TRUE)
+#' if (require("rstanarm", quietly = TRUE)) {
+#'   cor_test(iris, "Sepal.Length", "Sepal.Width", partial_bayesian = TRUE)
+#' }
 #' }
 #' @export
 cor_test <- function(data,
diff --git a/man/cor_test.Rd b/man/cor_test.Rd
index a4e18f39..b28684c2 100644
--- a/man/cor_test.Rd
+++ b/man/cor_test.Rd
@@ -274,6 +274,8 @@ cor_test(iris, "Sepal.Length", "Sepal.Width", partial = TRUE)
 if (require("lme4", quietly = TRUE)) {
   cor_test(iris, "Sepal.Length", "Sepal.Width", multilevel = TRUE)
 }
-cor_test(iris, "Sepal.Length", "Sepal.Width", partial_bayesian = TRUE)
+if (require("rstanarm", quietly = TRUE)) {
+  cor_test(iris, "Sepal.Length", "Sepal.Width", partial_bayesian = TRUE)
+}
 }
 }
diff --git a/tests/testthat/test-cor_test.R b/tests/testthat/test-cor_test.R
index ef5b36a4..60e1fafd 100644
--- a/tests/testthat/test-cor_test.R
+++ b/tests/testthat/test-cor_test.R
@@ -31,7 +31,7 @@ test_that("cor_test bayesian", {
 
   df <- iris
   df$Petal.Length2 <- df$Petal.Length
-  out3 <- cor_test(df, "Petal.Length", "Petal.Length2", bayesian = TRUE)
+  out3 <- suppressWarnings(cor_test(df, "Petal.Length", "Petal.Length2", bayesian = TRUE))
   expect_equal(out3$rho, 1.000, tolerance = 0.01)
 
   if (getRversion() >= "3.6") {
@@ -60,8 +60,8 @@ test_that("cor_test tetrachoric", {
   skip_if_not_or_load_if_installed("psych")
   skip_if_not_or_load_if_installed("polycor")
   data <- iris
-  data$Sepal.Width_binary <- ifelse(data$Sepal.Width > 3, 1, 0)
-  data$Petal.Width_binary <- ifelse(data$Petal.Width > 1.2, 1, 0)
+  data$Sepal.Width_binary <- as.numeric(data$Sepal.Width > 3)
+  data$Petal.Width_binary <- as.numeric(data$Petal.Width > 1.2)
 
   # With Factors / Binary
   out <- cor_test(data, "Sepal.Width_binary", "Petal.Width_binary", method = "tetrachoric")
@@ -184,6 +184,6 @@ test_that("cor_test one-sided p value", {
 # Edge cases --------------------------------------------------------------
 
 test_that("cor_test 2 valid observations", {
-  out <- correlation(data.frame(v2 = c(2, 1, 1, 2), v3 = c(1, 2, NA, NA)))
+  out <- suppressWarnings(correlation(data.frame(v2 = c(2, 1, 1, 2), v3 = c(1, 2, NA, NA))))
   expect_true(is.na(out$r))
 })