Visualization [GxP / QC / QA]

posted by Helmut Homepage – Vienna, Austria, 2021-09-18 17:26 (1006 d 03:59 ago) – Posting: # 22588
Views: 6,261

Hi ElMaestro,

❝ […] it makes very good sense to plot for example the RMSE, CV, SE of diff., or even the width of the CI as function of (cumulated) number of subjects.


If you have all data, of course. A simple visualization using the res data.frame of my previous post:

[image]




windows(width = 5.5, height = 5.5)
op <- par(no.readonly = TRUE)
par(mar = c(3, 4, 2, 0), cex.axis = 0.9, cex.main = 1, font.main = 1)
split.screen(c(length(CRO), length(metric)))
scrn <- 0
for (j in seq_along(CRO)) {
  for (k in seq_along(metric)) {
    scrn <- scrn + 1
    screen(scrn)
    plot(c(0.5, length(study)+0.5), rep(100, 2), type = "n",
         ylim = range(res$lower[res$CRO == CRO[j] & res$metric == metric[k]],
                      res$upper[res$CRO == CRO[j] & res$metric == metric[k]]),
         log = "y", xlab = "", ylab = "PE, 90% CI", axes = FALSE,
         main = paste0(CRO[j], ": ", metric[k]))
    axis(2, las = 1)
    axis(1, at = seq_along(study), tick = FALSE,
         labels = paste("n =", res$n[res$CRO == CRO[j] &
                               res$metric == metric[k]]))
    abline(h = c(80, 100, 125), col = c("red", "black", "red"))
    box()
    for (l in seq_along(study)) {
      arrows(x0 = l,
             y0 = res$lower[res$CRO == CRO[j] & res$metric == metric[k] &
                            res$study == study[l]],
             y1 = res$upper[res$CRO == CRO[j] & res$metric == metric[k] &
                            res$study == study[l]], length = 0.08,
             angle = 90, lwd = 2, code = 3)
      points(l, res$PE[res$CRO == CRO[j] & res$metric == metric[k] &
                       res$study == study[l]], pch = 19, cex = 1.25)
    }
  }
}
close.screen(all = TRUE)
par(op)


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