plotCiCalibrationEffect: Plot the effect of the CI calibration

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

Plot the effect of the CI calibration

Description

Creates a plot with the effect estimate on the x-axis and the standard error on the y-axis. The plot is trellised by true effect size. Negative and positive controls are shown as blue dots. The area below the dashed line indicated estimates that are statistically significant different from the true effect size (p < 0.05). The orange area indicates estimates with calibrated p < 0.05.

Usage

plotCiCalibrationEffect(
  logRr,
  seLogRr,
  trueLogRr,
  legacy = FALSE,
  model = NULL,
  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.
legacy	If true, a legacy error model will be fitted, meaning standard deviation is linear on the log scale. If false, standard deviation is assumed to be simply linear.
model	The fitted systematic error model. If not provided, it will be fitted on the provided data.
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.

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)))
plotCiCalibrationEffect(data$logRr, data$seLogRr, data$trueLogRr)

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