plotCalibrationEffect: Plot the effect of the calibration

In EmpiricalCalibration: Routines for Performing Empirical Calibration of Observational Study Estimates

Plot the effect of the calibration

Description

plotCalibrationEffect creates a plot showing the effect of the calibration.

Usage

plotCalibrationEffect(
  logRrNegatives,
  seLogRrNegatives,
  logRrPositives = NULL,
  seLogRrPositives = NULL,
  null = NULL,
  alpha = 0.05,
  xLabel = "Relative risk",
  title,
  showCis = FALSE,
  showExpectedAbsoluteSystematicError = FALSE,
  fileName = NULL,
  xLimits = c(0.25, 10),
  yLimits = c(0, 1.5)
)

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.
logRrPositives	Optional: A numeric vector of effect estimates of the positive controls on the log scale.
seLogRrPositives	Optional: The standard error of the log of the effect estimates of the positive controls.
null	An object representing the fitted null distribution as created by the fitNull or fitMcmcNull functions. If not provided, a null will be fitted before plotting.
alpha	The alpha for the hypothesis test.
xLabel	The label on the x-axis: the name of the effect estimate.
title	Optional: the main title for the plot
showCis	Show 95 percent credible intervals for the calibrated p = alpha boundary.
showExpectedAbsoluteSystematicError	Show the expected absolute systematic error. If null is of type mcmcNull the 95 percent credible interval will also be shown.
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.
xLimits	Vector of length 2 for limits of the plot x axis - defaults to 0.25, 10
yLimits	Vector of length 2 for size limits of the y axis - defaults to 0, 1.5

Details

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.

Value

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

Examples

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

EmpiricalCalibration documentation built on Sept. 30, 2024, 9:12 a.m.