Package index • EmpiricalCalibration

P-value calibration Functions for calibrating p-values based on an empirical null distribution estimated using negative controls.
`fitNull()`	Fit the null distribution
`fitMcmcNull()`	Fit the null distribution using MCMC
`fitNullNonNormalLl()`	Fit the null distribution using non-normal log-likelihood approximations
`computeTraditionalP()`	Compute the (traditional) p-value
`calibrateP()`	Calibrate the p-value
`plotMcmcTrace()`	Plot the MCMC trace
`plotForest()`	Create a forest plot
`plotCalibration()`	Create a calibration plot
`plotCalibrationEffect()`	Plot the effect of the calibration
`plotExpectedType1Error()`	Plot the expected type 1 error as a function of standard error
`computeExpectedAbsoluteSystematicError()`	Compute the expected absolute systematic error
`compareEase()`	Compare EASE of correlated sets of estimates
Confidence interval calibration Functions for calibrating confidence intervals based on a systematic error model fitted using negative and positive controls.
`fitSystematicErrorModel()`	Fit a systematic error model
`convertNullToErrorModel()`	Convert empirical null distribution to systematic error model
`computeTraditionalCi()`	Compute the (traditional) confidence interval
`calibrateConfidenceInterval()`	Calibrate confidence intervals
`plotTrueAndObserved()`	Plot true and observed values
`evaluateCiCalibration()`	Evaluate confidence interval calibration
`plotCiCalibration()`	Create a confidence interval calibration plot
`plotCiCalibrationEffect()`	Plot the effect of the CI calibration
`plotCiCoverage()`	Create a confidence interval coverage plot
`plotErrorModel()`	Plot the systematic error model
MaxSPRT and calibration Functions for performing empirical calibration when adjusting for sequential testing using MaxSPRT.
`calibrateLlr()`	Calibrate the log likelihood ratio
`computeCvBinomial()`	Compute critical values for Binomial data
`computeCvPoisson()`	Compute critical values for Poisson data
`computeCvPoissonRegression()`	Compute critical values for Poisson regression data
Data Data (real and simulated) for testing and demonstrating empirical calibration.
`sccs`	Incidence rate ratios from Self-Controlled Case Series
`caseControl`	Odds ratios from a case-control design
`cohortMethod`	Relative risks from a new-user cohort design
`southworthReplication`	Relative risks from an unadjusted new-user cohort design
`grahamReplication`	Relative risks from an adjusted new-user cohort design
`simulateControls()`	Simulate (negative) controls
`simulateMaxSprtData()`	Simulate survival data for MaxSPRT computation

Reference

P-value calibration

Confidence interval calibration

MaxSPRT and calibration

Data