plotCiCoverage: Create a confidence interval coverage plot

Description Usage Arguments Details Value Examples

View source: R/Plots.R

Description

plotCiCoverage creates a plot showing the coverage before and after confidence interval calibration at various widths of the confidence interval.

Usage

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plotCiCoverage(logRr, seLogRr, trueLogRr, strata = as.factor(trueLogRr),
  crossValidationGroup = 1:length(logRr), evaluation,
  legendPosition = "top", 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

The true log relative risk.

strata

Variable used to stratify the plot. Set strata = NULL for no stratification.

crossValidationGroup

What should be the unit for the cross-validation? By default the unit is a single control, but a different grouping can be provided, for example linking a negative control to synthetic positive controls derived from that negative control.

evaluation

A data frame as generated by the evaluateCiCalibration function. If provided, the logRr, seLogRr, trueLogRr, and strata arguments will be ignored.

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 plot showing the fraction of effects above, within, and below the confidence interval. The empirical calibration is performed using a leave-one-out design: The confidence interval of an effect is computed by fitting a null using all other controls. The plot shows the coverage for both theoretical (traditional) and empirically calibrated confidence intervals.

Value

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

Examples

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## Not run: 
data <- simulateControls(n = 50 * 3, mean = 0.25, sd = 0.25, trueLogRr = log(c(1, 2, 4)))
plotCiCoverage(data$logRr, data$seLogRr, data$trueLogRr)

## End(Not run)

OHDSI/EmpiricalCalibration documentation built on June 26, 2018, 7:12 a.m.