Plot the expected type 1 error as a function of standard error — plotExpectedType1Error • EmpiricalCalibration

plotExpectedType1Error creates a plot showing the expected type 1 error as a function of standard error.

plotExpectedType1Error(
  logRrNegatives,
  seLogRrNegatives,
  seLogRrPositives,
  alpha = 0.05,
  null = NULL,
  xLabel = "Relative risk",
  title,
  showCis = FALSE,
  showEffectSizes = FALSE,
  fileName = NULL
)

Arguments

logRrNegatives: A numeric vector of effect estimates of the negative controls on the log scale.
seLogRrNegatives: The standard error of the log of the effect estimates of the negative controls.
seLogRrPositives: The standard error of the log of the effect estimates of the positive controls.
alpha: The alpha (nominal type 1 error) to be used.
null: An object representing the fitted null distribution as created by the fitNull function. If not provided, a null will be fitted before plotting.
xLabel: If showing effect sizes, what label should be used for the effect size axis?
title: Optional: the main title for the plot
showCis: Show 95 percent credible intervals for the expected type 1 error.
showEffectSizes: Show the expected effect sizes alongside the expected type 1 error?
fileName: Name of the file where the plot should be saved, for example 'plot.png'. See the function ggsave in the ggplot2 package for supported file formats.

Value

A Ggplot object. Use the ggsave function to save to file.

Details

Creates a plot with the standard error on the x-axis and the expected type 1 error on the y-axis. The red line indicates the expected type 1 error given the estimated empirical null distribution if no calibration is performed. The dashed line indicated the nominal expected type 1 error rate, assuming the theoretical null distribution.

If standard errors are provided for non-negative estimates these will be plotted on the red line as yellow diamonds.

Examples

data(sccs)
negatives <- sccs[sccs$groundTruth == 0, ]
positive <- sccs[sccs$groundTruth == 1, ]
plotExpectedType1Error(negatives$logRr, negatives$seLogRr, positive$seLogRr)