plotCalibration: Create a calibration plot

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

Create a calibration plot

Description

plotCalibration creates a plot showing the calibration of our calibration procedure

Usage

plotCalibration(
  logRr,
  seLogRr,
  useMcmc = FALSE,
  legendPosition = "right",
  title,
  fileName = NULL
)

Arguments

logRr	A numeric vector of effect estimates on the log scale
seLogRr	The standard error of the log of the effect estimates. Hint: often the standard error = (log(<lower bound 95 percent confidence interval>) - log(<effect estimate>))/qnorm(0.025)
useMcmc	Use MCMC to estimate the calibrated P-value?
legendPosition	Where should the legend be positioned? ("none", "left", "right", "bottom", "top")
title	Optional: the main title for the plot
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.

Details

Creates a calibration plot showing the number of effects with p < alpha for every level of alpha. The empirical calibration is performed using a leave-one-out design: The p-value of an effect is computed by fitting a null using all other negative controls. Ideally, the calibration line should approximate the diagonal. The plot shows both theoretical (traditional) and empirically calibrated p-values.

Value

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

Examples

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

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