diagnostic_plots.R

# Diagnostic plots
diagPlots <- function(model){
  p1 <- ggplot(model, aes(.fitted, .resid)) +
    geom_point() + 
    stat_smooth(method = "loess") + 
    geom_hline(yintercept = 0, col="red", linetype = "dashed") +
    xlab("Fitted values") + 
    ylab("Residuals") +
    ggtitle("Residual vs Fitted Plot") + 
    theme_bw()
  
  p2 <- ggplot(model, aes(qqnorm(.stdresid)[[1]], .stdresid)) + 
    geom_point(na.rm = TRUE) +
    geom_abline(aes(qqline(.stdresid))) + 
    xlab("Theoretical Quantiles") + 
    ylab("Standardized Residuals") +
    ggtitle("Normal Q-Q") + 
    theme_bw()
  
  p3 <- ggplot(model, aes(.fitted, sqrt(abs(.stdresid)))) + 
    geom_point(na.rm = TRUE) +
    stat_smooth(method="loess", na.rm = TRUE) + 
    xlab("Fitted Value") +
    ylab(expression(sqrt("|Standardized residuals|"))) +
    ggtitle("Scale-Location") + 
    theme_bw()
  
  p4 <- ggplot(model, aes(seq_along(.cooksd), .cooksd)) + 
    geom_bar(stat="identity", position="identity") +
    xlab("Obs. Number")+ylab("Cook's distance") +
    ggtitle("Cook's distance") + 
    theme_bw()
  
  p5 <- ggplot(model, aes(.hat, .stdresid)) + 
    geom_point(aes(size = .cooksd), na.rm=TRUE) +
    stat_smooth(method = "loess", na.rm=TRUE) +
    xlab("Leverage") + 
    ylab("Standardized Residuals") +
    ggtitle("Residual vs Leverage Plot") +
    scale_size_continuous("Cook's Distance", range=c(1,5)) +
    theme_bw() + 
    theme(legend.position="bottom")
  
  p6 <- ggplot(model, aes(.hat, .cooksd)) + 
    geom_point(na.rm=TRUE) + 
    stat_smooth(method="loess", na.rm=TRUE) +
    xlab("Leverage hii")+ylab("Cook's Distance") +
    ggtitle("Cook's dist vs Leverage hii/(1-hii)") +
    geom_abline(slope=seq(0,3,0.5), color="gray", linetype="dashed") +
    theme_bw()
  
  return(list(rvfPlot=p1, qqPlot=p2, sclLocPlot=p3, cdPlot=p4, rvlevPlot=p5, cvlPlot=p6))
}