Color naive estimates black on both package forest plots and exercise…

R/plot.R

@@ -102,12 +102,31 @@ plot.outstandR <- function(x, ...,
     plot_df$Model <- factor(plot_df$Model, levels = model_levels)
   }
 
+  # Define custom colors so that any naive model is plotted in black
+  n_models <- length(model_levels)
+  is_naive <- grepl("Naive", model_levels, ignore.case = TRUE)
+  n_non_naive <- sum(!is_naive)
+
+  if (n_non_naive > 0) {
+    non_naive_colors <- grDevices::hcl(
+      h = seq(15, 375, length.out = n_non_naive + 1)[1:n_non_naive], 
+      c = 100, 
+      l = 65
+    )
+  } else {
+    non_naive_colors <- character(0)
+  }
+
+  model_colors <- stats::setNames(rep("black", n_models), model_levels)
+  model_colors[!is_naive] <- non_naive_colors
+
   # combined forest plot
   ggplot(
     plot_df, aes(x = .data$Estimate, y = .data$Treatments, color = .data$Model)) +
     geom_point(position = position_dodge(width = 0.5), size = 3) +
     geom_errorbarh(aes(xmin = .data$lower.0.95, xmax = .data$upper.0.95), 
                    position = position_dodge(width = 0.5), height = 0.2, na.rm = TRUE) +
+    scale_color_manual(values = model_colors) +
     facet_wrap(~.data$Type, scales = "free") +
     geom_vline(data = dplyr::filter(plot_df, .data$Type == "Relative Contrasts"), 
                aes(xintercept = 0), linetype = "dashed", color = "gray50") +

scripts/exercises2.qmd

@@ -341,9 +341,20 @@ all_results_intro$Method <- factor(all_results_intro$Method, levels = c(
 ```{r}
 #| echo: true
 
+# Define colors: naive is black, others are default ggplot2 colors
+methods_intro <- levels(all_results_intro$Method)
+is_naive_intro <- grepl("Naive", methods_intro, ignore.case = TRUE)
+n_non_naive_intro <- sum(!is_naive_intro)
+colors_intro <- stats::setNames(rep("black", length(methods_intro)), methods_intro)
+colors_intro[!is_naive_intro] <- grDevices::hcl(
+  h = seq(15, 375, length.out = n_non_naive_intro + 1)[1:n_non_naive_intro], 
+  c = 100, l = 65
+)
+
 ggplot(all_results_intro, aes(x = Estimate, y = Method, color = Method)) +
   geom_point(size = 4) +
   geom_errorbarh(aes(xmin = lower.0.95, xmax = upper.0.95), height = 0.2, linewidth = 1, na.rm = TRUE) +
+  scale_color_manual(values = colors_intro) +
   geom_vline(xintercept = 0, linetype = "dashed", color = "gray50", linewidth = 1) +
   theme_minimal() +
   labs(
@@ -696,9 +707,20 @@ all_results_final$Method <- factor(all_results_final$Method, levels = c(
   "G-comp ML (Anchored, Adjusted)"
 ))
 
+# Define colors dynamically: naive is black, others are default ggplot2 colors
+methods_final <- levels(all_results_final$Method)
+is_naive_final <- grepl("Naive", methods_final, ignore.case = TRUE)
+n_non_naive_final <- sum(!is_naive_final)
+colors_final <- stats::setNames(rep("black", length(methods_final)), methods_final)
+colors_final[!is_naive_final] <- grDevices::hcl(
+  h = seq(15, 375, length.out = n_non_naive_final + 1)[1:n_non_naive_final], 
+  c = 100, l = 65
+)
+
 ggplot(all_results_final, aes(x = Estimate, y = Method, color = Method)) +
   geom_point(size = 4) +
   geom_errorbarh(aes(xmin = lower.0.95, xmax = upper.0.95), height = 0.2, linewidth = 1, na.rm = TRUE) +
+  scale_color_manual(values = colors_final) +
 
   # Highlight True Effect (0.0) with a distinct line
   geom_vline(aes(xintercept = 0, linetype = "True Underlying Effect"), color = "red", linewidth = 1.2) +