density_plots_estimates.R

setwd("G:/Epidata Share/9) Tali Analyses/THESIS/propensity_scores/simulation study")
data1<-read.csv("0_output_unconfounded.csv")
data2<-read.csv("2_output_sim_yoshida.csv")
data3<-read.csv("3_output_sim_adjust.csv")
data4<-read.csv("4_output_sim_matched_pairwise.csv")
data5<-read.csv("4_output_sim_matched_pairwise_andcontrol.csv")

mean1<-mean(data1$exp.1)
mean2<-mean(data2$exp.1)
mean3<-mean(data3$exp.1)
mean4<-mean(data4$exp.1)
mean5<-mean(data5$exp.1)


pdf("density_plot_exposure1.pdf")
plot(density(log(data2$exp.1)),col="cyan" , lty=1,ylim=c(0,5), main="Distribution of Hazards Ratios, exp=2")
 abline(v=log(mean2), col="cyan")
lines(density(log(data3$exp.1)), col="purple", lty=1)
abline(v=log(mean3), col="purple", lty=1)
lines(density(log(data4$exp.1)), col="green", lty=2)
abline(v=log(mean4), col="green", lty=2)
legend("topright", c("weights","adjusting","matched", "truth"), col=c( "cyan", "purple", "green","black"), lty=c(1,1,2,2))
abline(v=log(1.5), lty=2)
dev.off()



mean1<-mean(data1$exp.2)
mean2<-mean(data2$exp.2)
mean3<-mean(data3$exp.2)
mean4<-mean(data4$exp.2)



pdf("density_plot_exposure2.pdf")
plot(density(log(data2$exp.2)),col="cyan" , lty=1,ylim=c(0,5), main="Distribution of Hazards Ratios, exp=2")
abline(v=log(mean2), col="cyan")
lines(density(log(data3$exp.2)), col="purple", lty=1)
abline(v=log(mean3), col="purple", lty=1)
lines(density(log(data4$exp.2)), col="green", lty=2)
abline(v=log(mean4), col="green", lty=2)
legend("topright", c("weights","adjusting","matched", "truth"), col=c( "cyan", "purple", "green","black"), lty=c(1,1,2,2))
abline(v=log(1.5), lty=2)
dev.off()