plotEmpiricalNulls: Plot empirical null distributions

Description

Plot the empirical null distribution for multiple data sources.

Usage

plotEmpiricalNulls(
  logRr,
  seLogRr,
  labels,
  xLabel = "Relative risk",
  limits = c(0.1, 10),
  showCis = TRUE,
  fileName = NULL
)

Value

A Ggplot object. Use the ggplot2::ggsave() function to save to file.

Arguments

logRr: A numeric vector of effect estimates for the negative controls 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) - l og(effect estimate))/qnorm(0.025).
labels: A vector containing the labels for the various sources. Should be of equal length as logRr and seLogRr.
xLabel: The label on the x-axis: the name of the effect estimate.
limits: The limits of the effect size axis.
showCis: Show the 95 percent confidence intervals on the null distribution and distribution parameter estimates?
fileName: Name of the file where the plot should be saved, for example 'plot.png'. See the function ggplot2::ggsave() for supported file formats.

Details

Creates a plot showing the empirical null distributions. Distributions are shown as mean plus minus one standard deviation, as well as a distribution plot.

Examples

Run this code

# Some example data:
site1 <- EmpiricalCalibration::simulateControls(n = 50, mean = 0, sd = 0.1, trueLogRr = 0)
site1$label <- "Site 1"
site2 <- EmpiricalCalibration::simulateControls(n = 50, mean = 0.1, sd = 0.2, trueLogRr = 0)
site2$label <- "Site 2"
site3 <- EmpiricalCalibration::simulateControls(n = 50, mean = 0.15, sd = 0.25, trueLogRr = 0)
site3$label <- "Site 3"
sites <- rbind(site1, site2, site3)

plotEmpiricalNulls(logRr = sites$logRr, seLogRr = sites$seLogRr, labels = sites$label)