calibrateConfidenceInterval: Calibrate confidence intervals

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

Calibrate confidence intervals

Description

Calibrate confidence intervals

Usage

calibrateConfidenceInterval(logRr, seLogRr, model, ciWidth = 0.95)

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).
model	An object of type systematicErrorModel as created by the fitSystematicErrorModel function.
ciWidth	The width of the confidence interval. Typically this would be .95, for the 95 percent confidence interval.

Details

Compute calibrated confidence intervals based on a model of the systematic error.

Value

A data frame with calibrated confidence intervals and point estimates.

Examples

data <- simulateControls(n = 50 * 3, mean = 0.25, sd = 0.25, trueLogRr = log(c(1, 2, 4)))
model <- fitSystematicErrorModel(data$logRr, data$seLogRr, data$trueLogRr)
newData <- simulateControls(n = 15, mean = 0.25, sd = 0.25, trueLogRr = log(c(1, 2, 4)))
result <- calibrateConfidenceInterval(newData$logRr, newData$seLogRr, model)
result

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