require(ggplot2)
## Loading required package: ggplot2
require(scales)
## Loading required package: scales
library(Hmisc)
## Loading required package: grid
## Loading required package: lattice
## Warning: package 'lattice' was built under R version 3.1.3
## Loading required package: survival
## Loading required package: splines
## Loading required package: Formula
## 
## Attaching package: 'Hmisc'
## 
## The following objects are masked from 'package:base':
## 
##     format.pval, round.POSIXt, trunc.POSIXt, units
require(grid)

setwd("~/Google Drive/work/DG paper/Cost_benefit writing/2. experiment multiplier study/analysis/data")
temp = read.csv("cleaned_data_400.csv")


table(temp$benefit_cost_ratio)
## 
##     1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 2/1 3/1 4/1 5/1 6/1 7/1 8/1 9/1 
##   7  29  23  20  27  17  22  28  17  24  23  21  20  21  25  31  29  16

Selfish Actor percentage

temp$Benefit_Cost_Ratio <- factor(temp$benefit_cost_ratio,levels=c("9/1","8/1","7/1","6/1","5/1","4/1","3/1","2/1","1/1","1/2","1/3","1/4","1/5","1/6","1/7","1/8","1/9"),labels=c("9/1","8/1","7/1","6/1","5/1","4/1","3/1","2/1","1/1","1/2","1/3","1/4","1/5","1/6","1/7","1/8","1/9"));

temp = subset(temp, !is.na(temp$Benefit_Cost_Ratio))
#selfish 
temp$selfish[temp$MU_shared == 0 & !is.na(temp$MU_shared)] <- 1
temp$selfish[!temp$MU_shared == 0 & !is.na(temp$MU_shared)]  <- 0

graph1 <- ggplot(temp, aes(x=Benefit_Cost_Ratio, y=selfish,fill=factor(Benefit_Cost_Ratio)))+ 
  stat_summary(fun.y = mean, geom = "bar",colour="black")+ 
  stat_summary(fun.data = mean_cl_normal, geom = "errorbar",width=.4) + 
  labs(x ="Benefit_Cost_Ratio", y = "Percentage of\n Selfish Actors") + theme(legend.position="none")+
  coord_cartesian() 

graph1  
## Warning: Removed 1 rows containing missing values (stat_summary).
## Warning: Removed 1 rows containing missing values (stat_summary).

Donation by only Prosocial actors

graph2 <- ggplot(temp[temp$MU_shared >0 ,], aes(x=Benefit_Cost_Ratio, y=MU_shared,fill=factor(Benefit_Cost_Ratio)))+ 
  stat_summary(fun.y = mean, geom = "bar",colour="black")+ 
  stat_summary(fun.data = mean_cl_normal, geom = "errorbar",width=.4) +  
  labs(x ="Benefit_Cost_Ratio", y = "Donation by Prosocial Actors") + theme(legend.position="none")+
  coord_cartesian() 

graph2
## Warning: Removed 18 rows containing missing values (stat_summary).
## Warning: Removed 18 rows containing missing values (stat_summary).

Donation by all actors

graph3 <- ggplot(temp, aes(x=Benefit_Cost_Ratio, y=MU_shared,fill=factor(Benefit_Cost_Ratio)))+ 
  stat_summary(fun.y = mean, geom = "bar",colour="black")+ 
  stat_summary(fun.data = mean_cl_normal, geom = "errorbar",width=.4) + ylim(0,80) + 
  labs(x ="Benefit_Cost_Ratio", y = "Donation by All Actors") + theme(legend.position="none")+
  coord_cartesian() 

graph3 
## Warning: Removed 39 rows containing missing values (stat_summary).
## Warning: Removed 39 rows containing missing values (stat_summary).

Donation distribution for different benefit/cost ratio

ratio = c('9/1',"8/1","7/1", "6/1", "5/1", "4/1", "3/1", "2/1", "1/1", "1/2", "1/3", "1/4", "1/5", "1/6", "1/7", "1/8", "1/9")

for (i in 1:17){
  a = ggplot(temp[temp$benefit_cost_ratio== ratio[i],], aes(x=MU_shared, y = ..count../sum(..count..)))+ scale_y_continuous(labels = percent_format(), limits = c(0, 1), breaks = seq(0, 0.8, 0.2)) + geom_bar(position="dodge",binwidth=5) + scale_x_continuous(limits = c(0,100)) + labs(x =paste ("Benefit/Cost Ratio: ", ratio[i]), y = "Percentage of\nParicipants")
  print (a)
}