Routines for performing empirical calibration of observational study estimates. By using a set of negative control hypotheses we can estimate the empirical null distribution of a particular observational study setup. This empirical null distribution can be used to compute a calibrated p-value, which reflects the probability of observing an estimated effect size when the null hypothesis is true taking both random and systematic error into account.
This R package contains routines for performing empirical calibration of observational study estimates. By using a set of negative control hypotheses we can estimate the empirical null distribution of a particular observational study setup. This empirical null distribution can be used to compute a calibrated p-value, which reflects the probability of observing an estimated effect size when the null hypothesis is true taking both random and systematic error into account, as described in the paper [Interpreting observational studies: why empirical calibration is needed to correct p-values.] (http://dx.doi.org/10.1002/sim.5925).
data(sccs) #Load one of the included data setsnegatives <- sccs[sccs$groundTruth == 0,] #Select the negative controlsnull <- fitNull(negatives$logRr,negatives$seLogRr) #Fit the null distributionpositive <- sccs[sccs$groundTruth == 1,] #Select the positive control
plotCalibrationEffect(negatives$logRr,negatives$seLogRr,positive$logRr,positive$seLogRr,null) #Compute the calibrated p-value:calibrateP(positive$logRr,positive$seLogRr, null) #Compute calibrated p-value[1] 0.8390598
This is a pure R package.
Requires R (version 3.1.0 or newer).
In R, use the following commands to install the latest stable version from CRAN:
install.packages("EmpiricalCalibration")
To install the latest development version directly from GitHub, use:
install.packages("devtools")library(devtools)install_github("ohdsi/EmpiricalCalibration")
EmpiricalCalibration is licensed under Apache License 2.0
This package has been developed in RStudio. ###Development status
This package is ready for use.
Martijn Schuemie is the author of this package.
NEW FEATURES
Ability to add credible intervals to calibration effect plot
Plot CI calibration (using leave-one-out cross-validation)
BUG FIXES
Fixed vignette name in index
Removed coverage plot (moved to MethodEvaluation package)
Changes: initial submission to CRAN