Update 07/02/2023

Author: berntgl

DESCRIPTION

@@ -10,4 +10,6 @@ Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.2.1
 Imports: 
     dplyr,
-    ggplot2
+    ggplot2,
+    grid,
+    gridExtra

LICENSE

@@ -1,2 +1,2 @@
-YEAR: 2022
-COPYRIGHT HOLDER: fxsizedistr authors
+YEAR: 2023
+COPYRIGHT HOLDER: ESDist authors

LICENSE.md

@@ -1,6 +1,6 @@
 # MIT License
 
-Copyright (c) 2022 ESDist authors
+Copyright (c) 2023 ESDist authors
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

R/esd_plot.R

@@ -4,18 +4,21 @@
 #' @param es Column name of effect sizes
 #' @param es_type A string describing the type of effect size used (e.g.,
 #'   "Cohen's d")
-#' @param method Defaults to 'none', can also be 'thirds' for 16.65th, 50th, and
+#' @param method Defaults to FALSE, can also be 'thirds' for 16.65th, 50th, and
 #'   83.35th percentiles, or 'quads' for 25th, 50th, and 75th percentiles.
-#' @param bin_width Sets the bin width for the histogram
-#' @param pop_es A numeric argument that corresponds to the population ES of
+#' @param mean Defaults to FALSE, but will insert a ggplot geom_vline element
+#'   that corresponds to the mean effect size
+#' @param pop_es #' @param pop_es A numeric argument that corresponds to the population ES of
 #'   interest. This will split the histogram into two parts around the inputted
 #'   value.
+#' @param bin_width Numeric argument that corresponds to the bin width for the
+#'   histogram. Defaults to 0.1
 #'
 #' @return A ggplot object
 #' @export
 #'
 #' @examples esd_plot(df, es, es_type = "Cohen's d", method = "thirds", pop)
-esd_plot <- function(df, es, es_type, pop_es = NULL, method = FALSE, mean = FALSE, bin_width = 0.1) {
+esd_plot <- function(df, es, es_type, method = FALSE, mean = FALSE, pop_es = NULL, bin_width = 0.1) {
   es_col <- df[, deparse(substitute(es))]
 
   if (missing(pop_es)){

R/esd_plot_group.R

@@ -0,0 +1,112 @@
+#' Creating an ESD plot per group
+#'
+#' @param df Dataset
+#' @param es Column name of effect sizes
+#' @param es_type A string describing the type of effect size used (e.g.,
+#'   "Cohen's d")
+#' @param grouping_var Column name of grouping variable
+#' @param method Defaults to FALSE, but can be 'quads' or 'thirds'
+#' @param mean Defaults to FALSE, but will insert a ggplot geom_vline element
+#'   that corresponds to the mean effect size
+#' @param pop_es A numeric argument that corresponds to the population ES of
+#'   interest. This will split the histogram into two parts around the inputted
+#'   value.
+#' @param bin_width Numeric argument that corresponds to the bin width for the
+#'   histogram. Defaults to 0.1
+#'
+#' @return A ggplot element
+#' @export
+#'
+#' @examples
+esd_plot_group <- function(df, es, es_type, grouping_var, method = FALSE, mean = FALSE, pop_es = NULL, bin_width = 0.1) {
+  es_col <- df[, deparse(substitute(es))]
+
+  dat_b <- df %>%
+    group_by({{grouping_var}}) %>%
+    mutate(mean = mean({{es}}),
+           q16 = quantile({{es}}, prob = 0.1665),
+           q25 = quantile({{es}}, prob = 0.25),
+           q50 = quantile({{es}}, prob = 0.50),
+           q75 = quantile({{es}}, prob = 0.75),
+           q83 = quantile({{es}}, prob = 0.8335),) %>%
+    ungroup()
+  q16_label <- "16.65th"
+  q25_label <- "25th"
+  q50_label <- "50th"
+  q75_label <- "75th"
+  q83_label <- "83.35th"
+
+  if (missing(pop_es)){
+    plot <- ggplot(data = dat_b)+
+      geom_histogram(aes({{es}}), fill = "#355C7D", binwidth = bin_width)+
+      scale_x_continuous(breaks = seq(0, 5, 0.5)) +
+      labs(x = es_type, y = "Frequency")+
+      theme_minimal() +
+      facet_grid(vars({{grouping_var}}),
+                 switch = "y")+
+      theme(axis.text = element_text(size=12),
+            axis.title = element_text(size=20),
+            strip.text.y.left = element_text(angle = 0,
+                                             size = 12),
+            legend.position = "bottom")
+  } else {
+    rank <- length(es_col[es_col <= pop_es])/length(es_col) * 100
+    rank_rev <- 100 - rank
+
+    rank_perc <- sprintf("%.2f%%", rank)
+    rank_rev_perc <- sprintf("%.2f%%", rank_rev)
+
+    plot <- ggplot(data = dat_b) +
+      geom_histogram(aes(es_col, fill = stat(x) > pop_es), binwidth = bin_width) +
+      scale_fill_manual(name = sprintf("ES < or > %.2f", pop_es),
+                        labels = c(rank_perc, rank_rev_perc),
+                        values = c("#EEE0CB", "#355C7D")) +
+      labs(x = es_type, y = "Frequency")+
+      theme_minimal()+
+      facet_grid(vars({{grouping_var}}),
+                 switch = "y")+
+      theme(axis.text = element_text(size=12),
+            axis.title = element_text(size=20),
+            strip.text.y.left = element_text(angle = 0,
+                                             size = 12),
+            legend.position = "bottom")
+  }
+  if (!isFALSE(method)) {
+    if (method == "quads") {
+      plot <- plot +
+        geom_vline(aes(xintercept = q25, color = "q25"), linetype = "dashed", size = 1) +
+        geom_vline(aes(xintercept = q50, color = "q50"), linetype = "dashed", size = 1) +
+        geom_vline(aes(xintercept = q75, color = "q75"), linetype = "dashed", size = 1) +
+        scale_color_manual(name = "Percentiles",
+                           values = c(q25 = "#F8B195",
+                                      q50 = "#F67280",
+                                      q75 = "#C06C84",
+                                      q4 = "#7DAA92"),
+                           labels = c(q25_label, q50_label, q75_label, "Mean"))
+      } else if (method == "thirds") {
+        plot <- plot+
+          geom_vline(aes(xintercept = q16, color = "q16"), linetype = "dashed", size = 1) +
+          geom_vline(aes(xintercept = q50, color = "q50"), linetype = "dashed", size = 1) +
+          geom_vline(aes(xintercept = q83, color = "q83"), linetype = "dashed", size = 1) +
+          scale_color_manual(name = "Percentiles",
+                             values = c(q16 = "#F8B195",
+                                        q50 = "#F67280",
+                                        q83 = "#C06C84",
+                                        q4 = "#7DAA92"),
+                             labels = c(q16_label, q50_label, q83_label, "Mean"))
+      } else {
+        return("Please enter a valid method")
+      }
+  } else if (isFALSE(method)) {
+    plot <- plot
+  } else {
+    return("Please enter a valid method")
+  }
+  if (mean == TRUE) {
+    plot <- plot +
+      geom_vline(aes(xintercept = mean, color = "q4"), linetype = "dotted", size = 1)
+  } else {
+    plot <- plot
+  }
+ return(plot)
+}