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95% Confidence Interval

Example

Code Used

# Using the Monolix data set 'Bolus' to show what the 'ci95.whisker' can do

#pdf(file="F:/Website/blocks/confidence-large.pdf", width = 15, height = 7.5)
### Import Data  
  data <- bolus
  split.column <- "DOSE"

  data <- data[data$DOSE == 120000,]

  data.select <- data[ data$MDV == 0 & data$AMT == 0, ] 
    ### Rows where MDV == 0 and AMT == 0  (Good Rows for plotting x,y)
    
  data.to.plot <- list()
  
  data.to.plot$x <- data.select[,"TIME"]  #x
  data.to.plot$y <- data.select[,"DV"]  #y
  data.to.plot$ids <- data.select[,"ID"]  #ids
  
  data.to.plot$criteria <- data.select[,split.column]

  x.min.lim <- 0
  x.max.lim <- 10
  y.min.lim <- 0
  y.max.lim <- max(data.to.plot[["y"]])
  data.to.plot$x.lim <- c(x.min.lim,x.max.lim)
  data.to.plot$y.lim <- c(y.min.lim,y.max.lim)

  bw <- FALSE

  library(lattice)
### End Import


### Panel Function

  function.of.panel <- function(
    x,
    y,
    groups = groups,
    data.to.plot.in.panel = data.to.plot,
    black.and.white.in.panel = bw,
    subscripts
  ){
  cat("\n\n\nPacket", packet.number(),"\n")
  
  ### Grid
    plot.grid(
      x.divisions = 10,
      y.divisions = 10,
      grid.color = "grey95",
      x.limits = data.to.plot.in.panel[["x.lim"]],
      y.limits = data.to.plot.in.panel[["y.lim"]]
    )

  ### Plot CI
    plot.ci95.whisker(
      points.x = x, 
      points.y = y, 
      distribution = "normal", #"normal"
      y.limits = data.to.plot.in.panel[["y.lim"]],
      ci95.ghost = .5,
      whiskers.and.outliers = TRUE
    )

  }

      
### End Panel



### Make Scatter Plot
  lat.ci <- xyplot(
    y ~ x | as.factor(criteria), 
      # Remove '| as.factor(criteria)' if you do not want to split the data
    data = data.to.plot,
    type = NULL,
      # Taken Care of in Panel
    aspect=.5,
      # X is twice as long as Y
    groups = ids,
    xlab = "Time [units]",
    ylab = "Response [units]",
    xlim = c(x.min.lim - 0.03*(x.max.lim-x.min.lim)*0.5,x.max.lim + 0.03*(x.max.lim-x.min.lim)*0.5), 
      #0.5 is to compensate for the aspect ratio (aspect)
    ylim = c(y.min.lim - 0.03*(y.max.lim-y.min.lim), y.max.lim + 0.03*(y.max.lim-y.min.lim)),
    main = "95% Confidence Interval Example",
    panel = function.of.panel,

    key = list(
      title = "Legend",
      text = list(
        c("Box and Whisker Outliers"),
        col="black"
      ),
      points = list(
        col = c("black"),
        pch = c(1),
        cex = c(1.5)*0.75
      ),
      type = "l",
      space = "right",
      cex.title = 1,
      cex = 0.75
    )

  )

### Change Color of Trellis Device and Plot Data
  trellis.device(color = !bw,new = FALSE,retain = FALSE)

### Plot Data
  print(lat.ci)

#dev.off()