visualize distributions

Scripts/visualize_distr_spli.R

@@ -16,6 +16,38 @@ models <- list(
   "Treated Pred" = MXL_wtp_Treated_Pred_model
 )
 
+group_color_mapping <- c(
+  "Control" = "grey",
+  "Treated" = "red",
+  "Optional" = "yellow"
+)
+
+# Define line type mapping for prediction status
+prediction_line_mapping <- c(
+  "Not Predicted" = "dashed",
+  "Predicted" = "solid"
+)
+
+# Create a mapping for the groups
+group_mapping <- c(
+  "Control Not Pred" = "Control",
+  "Control Pred" = "Control",
+  "Treated Not Pred" = "Treated",
+  "Treated Pred" = "Treated",
+  "Opt Not Pred" = "Optional",
+  "Opt Pred" = "Optional"
+)
+
+# Create a mapping for prediction status
+prediction_mapping <- c(
+  "Control Not Pred" = "Not Predicted",
+  "Control Pred" = "Predicted",
+  "Treated Not Pred" = "Not Predicted",
+  "Treated Pred" = "Predicted",
+  "Opt Not Pred" = "Not Predicted",
+  "Opt Pred" = "Predicted"
+)
+
 # Define the x-range for plotting (1000 values)
 x_range <- seq(-20, 100, length.out = 1000)
 
@@ -36,22 +68,32 @@ for (i in seq_along(models)) {
   y <- dnorm(x_range, mean, sd)
   
   # Create a data frame for this model and append it to the main data frame
-  temp_data <- data.frame(x = x_range, density = y, model = model_name)
+  temp_data <- data.frame(
+    x = x_range, 
+    density = y, 
+    model = model_name,
+    Group = group_mapping[[model_name]],
+    Prediction = prediction_mapping[[model_name]]
+  )
+  
   plot_data <- bind_rows(plot_data, temp_data)
 }
 
-# Plot using ggplot2
-ggplot(plot_data, aes(x = x, y = density, color = model)) +
-  geom_line() + 
+# Plot using ggplot2 with custom color and linetype mappings
+ggplot(plot_data, aes(x = x, y = density, color = Group, linetype = Prediction)) +
+  geom_line(size = 1) + 
+  scale_color_manual(values = group_color_mapping) +  # Set custom colors for groups
+  scale_linetype_manual(values = prediction_line_mapping) +  # Set custom linetypes for prediction status
   labs(
     title = "Normal Distributions from Multiple MXL Models",
-    x = "x",
+    x = "WTP Naturalness (€/month)",
     y = "Density",
-    color = "Model"
+    color = "Group",
+    linetype = "Prediction"
   ) +
   theme_minimal() +
-  theme(legend.position = "right") +
-  scale_color_brewer(palette = "Set1")
+  theme(legend.position = "right")
+
 
 #### Z-test if distributions are different