plotCalibrationEffect creates a plot showing the effect of the calibration.
plotCalibrationEffect( logRrNegatives, seLogRrNegatives, logRrPositives = NULL, seLogRrPositives = NULL, null = NULL, alpha = 0.05, xLabel = "Relative risk", title, showCis = FALSE, fileName = NULL )
A numeric vector of effect estimates of the negative controls on the log scale.
The standard error of the log of the effect estimates of the negative controls.
Optional: A numeric vector of effect estimates of the positive controls on the log scale.
Optional: The standard error of the log of the effect estimates of the positive controls.
An object representing the fitted null distribution as created by the
The alpha for the hypothesis test.
The label on the x-axis: the name of the effect estimate.
Optional: the main title for the plot
Show 95 percent credible intervals for the calibrated p = alpha boundary.
Name of the file where the plot should be saved, for example 'plot.png'.
See the function
A Ggplot object. Use the
ggsave function to save to file.
Creates a plot with the effect estimate on the x-axis and the standard error on the y-axis. Negative controls are shown as blue dots, positive controls as yellow diamonds. The area below the dashed line indicated estimates with p < 0.05. The orange area indicates estimates with calibrated p < 0.05.
data(sccs) negatives <- sccs[sccs$groundTruth == 0, ] positive <- sccs[sccs$groundTruth == 1, ] plotCalibrationEffect(negatives$logRr, negatives$seLogRr, positive$logRr, positive$seLogRr)