ADDINS.txt

library(ggplot2)
library(dplyr)
library(readr)
library(MethComp)
data(milk)


Method1 <- milk %>% filter(meth=="Trig") %>% pull(y)
Method2 <- milk %>% filter(meth=="Gerber") %>% pull(y)


  Dif = Method1-Method2 
  Avg = 0.5*(Method1+Method2)
  BAplotDF = data.frame(Method1,Method2,Avg,Dif)


MCS_plot_1 <- ggplot(BAplotDF, aes(x = Method1, y = Method2)) +
    geom_point(alpha = 0.75,size=2.5) +
    geom_abline(intercept=0,slope=1, colour = "#CC6666", lwd=1,lty=2)+
    stat_smooth(method="lm",se=FALSE, colour = "blue", lwd=1,lty=3) + 
    ylab("Trig") +
    xlab("Gerber")  + theme_bw() + ggtitle("Milk Data: Identity Plot") +theme(
     axis.title.y = element_text(colour="grey20",size=14,face="bold"),
     axis.text.x = element_text(colour="grey20",size=14,face="bold"),
     axis.text.y = element_text(colour="grey20",size=14,face="bold"),  
     axis.title.x = element_text(colour="grey20",size=14,face="bold"))

MCS_plot_2 <-  ggplot(BAplotDF, aes(x = Avg, y = Dif)) +
    geom_point(alpha = 0.75,size=2) +
    geom_hline(yintercept = mean(BAplotDF$Dif), colour = "#9999CC", lwd=1.25) +
    geom_hline(yintercept = mean(BAplotDF$Dif) - (1.96 * sd(BAplotDF$Dif)), colour = "#CC6666", lwd=1.25, lty=2) +
    geom_hline(yintercept = mean(BAplotDF$Dif) + (1.96 * sd(BAplotDF$Dif)), colour = "#CC6666", lwd=1.25,lty=2) +
    geom_hline(yintercept = 0, colour = "black", lty=3, size = 0.5) +
    ylab("Casewise Differences") +
    xlab("Casewise Averages")  + theme_bw() + theme_bw() + ggtitle("Milk Data: Bland-Altman Plot") +theme(
     axis.title.y = element_text(colour="grey20",size=14,face="bold"),
     axis.text.x = element_text(colour="grey20",size=14,face="bold"),
     axis.text.y = element_text(colour="grey20",size=14,face="bold"),  
     axis.title.x = element_text(colour="grey20",size=14,face="bold"))
  

Milk_MCS <- grid.arrange( MCS_plot_1, MCS_plot_2, ncol=1)


ggsave(filename = "Milk_MCS.png", Milk_MCS,      width = 10, height = 8, dpi = 300, units = "in", device='png')