plotForest: Create a forest plot

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

Create a forest plot

Description

plotForest creates a forest plot of effect size estimates.

Usage

plotForest(
  logRr,
  seLogRr,
  names,
  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)
names	A vector containing the names of the drugs or outcomes
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 1 (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(sccs)
negatives <- sccs[sccs$groundTruth == 0, ]
plotForest(negatives$logRr, negatives$seLogRr, negatives$drugName)

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