plotTrueAndObserved: Plot true and observed values

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

Plot true and observed values

Description

Plot true and observed values, for example from a simulation study.

Usage

plotTrueAndObserved(
  logRr,
  seLogRr,
  trueLogRr,
  xLabel = "Relative risk",
  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).
trueLogRr	A vector of the true effect sizes.
xLabel	The label on the x-axis: the name of the effect estimate.
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 forest plot of effect size estimates (ratios). Estimates that are significantly different from the true value (alpha = 0.05) are marked in orange, others are marked in blue.

Value

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

Examples

data <- simulateControls(n = 50 * 3, mean = 0.25, sd = 0.25, trueLogRr = log(c(1, 2, 4)))
plotTrueAndObserved(data$logRr, data$seLogRr, data$trueLogRr)

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