Update app.R

app.R

@@ -5,6 +5,7 @@
 options(error = NULL)
 library(shiny)
 library(ggplot2)
+library(ggthemes)
 library(strategize)
 library(dplyr)
 
@@ -29,18 +30,60 @@ plot_factor <- function(pi_star_list,
   }))
   
   # Plot with ggplot2
-  p <- ggplot(df, aes(x = Level, y = Probability, fill = Strategy)) +
-    geom_bar(stat = "identity", position = position_dodge(width = 0.9), width = 0.8) +
-    #geom_errorbar(aes(ymin = Probability - zStar * SE, ymax = Probability + zStar * SE),
-                  #position = position_dodge(width = 0.9), width = 0.25) +
-    labs(title = paste("Optimal Distribution for", factor_name),
-         x = "Level", y = "Probability") +
-    theme_minimal() +
-    theme(axis.text.x = element_text(angle = 45, hjust = 1),
-          legend.position = "top") +
-    scale_fill_manual(values = c("Democrat" = "#89cff0", 
-                                 "Republican" = "red",
-                                 "Optimal" = "black"))
+  p <- ggplot(df, aes(x = Level, y = Probability, color = Strategy)) +
+    # Thin segment from y=0 to y=Probability
+    geom_segment(
+      aes(xend = Level, y = 0, yend = Probability),
+      position = position_dodge(width = 0.7),
+      size = 0.3
+    ) +
+    # Point at the probability
+    geom_point(
+      position = position_dodge(width = 0.7),
+      size = 2.5
+    ) +
+    # Optional text label for the probability value above the point
+    geom_text(
+      aes(label = sprintf("%.2f", Probability)),
+      position = position_dodge(width = 0.7),
+      vjust = -0.7,
+      size = 3
+    ) +
+    # If you want error bars, re-activate lines below and adjust as desired
+    # geom_errorbar(
+    #   aes(ymin = Probability - zStar * SE, ymax = Probability + zStar * SE),
+    #   position = position_dodge(width = 0.7),
+    #   width = 0.2,
+    #   size = 0.3
+    # ) +
+    
+    # Labels
+    labs(
+      title = sprintf("Optimal Distribution for *%s*", 
+                      gsub(factor_name,pattern = "\\.",replace=" ")),
+      x = "Level",
+      y = "Probability"
+    ) +
+    
+    # Apply Tufte's minimalistic theme
+    #theme_tufte(base_size = 12) +
+    theme_minimal(base_size = 16,
+                  base_line_size = 0) +
+    theme(
+      legend.position = "none",
+      legend.title    = element_blank(),
+      # Remove or soften grid lines
+      panel.grid.major = element_blank(),
+      panel.grid.minor = element_blank(),
+      # Keep a minimal axis line
+      axis.line = element_line(color = "black", size = 0.3),
+      axis.text.x = element_text(angle = 45, hjust = 1)
+    ) +
+    
+    # Manual color scale for different strategies
+    scale_color_manual(values = c("Democrat"   = "#89cff0",
+                                  "Republican" = "red",
+                                  "Optimal"    = "black"))
   
   return(p)
 }
@@ -98,12 +141,19 @@ ui <- fluidPage(
                  plotOutput("strategy_plot", height = "600px")),
         tabPanel("Q Value",
                  verbatimTextOutput("q_value"),
-                 p("Q represents the estimated outcome (e.g., selection probability) under the optimal strategy, with 95% confidence interval.")),
+                 p("Q represents the estimated outcome (e.g., strategy probability)
+                   under the optimal strategy, with 95% confidence interval.")),
         tabPanel("About",
-                 h3("About This App"),
-                 p("This Shiny app explores the `strategize` package using Ono experimental data. It computes optimal strategies for Average (optimizing for a respondent group) and Adversarial (optimizing for both parties in competition) cases on the fly."),
-                 p("**Average Case**: Optimizes candidate characteristics for a selected respondent group."),
-                 p("**Adversarial Case**: Finds equilibrium strategies for Democrats and Republicans, identified by 'Pro-life' stance.")
+                 h3("About this page"),
+                 p("This page app explores the ",
+                   a("strategize R package", href = "https://github.com/cjerzak/strategize-software/", target = "_blank"), 
+                   " R package using Ono forced conjoint experimental data. 
+                   It computes optimal strategies for Average (optimizing for a respondent group) 
+                   and Adversarial (optimizing for both parties in competition) cases on the fly."),
+                 p(strong("Average Case:"), 
+                   "Optimizes candidate characteristics for a selected respondent group."),
+                 p(strong("Adversarial Case"),
+                   "Finds equilibrium strategies for Democrats and Republicans.")
         )
       ),
       br(),