EmpiricalCalibration: Routines for Performing Empirical Calibration of Observational Study Estimates

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. A similar approach can be used to calibrate confidence intervals, using both negative and positive controls. For more details, see Schuemie et al. (2013) <doi:10.1002/sim.5925> and Schuemie et al. (2018) <doi:10.1073/pnas.1708282114>.

Package details

AuthorMartijn Schuemie [aut, cre] (<https://orcid.org/0000-0002-0817-5361>), Marc Suchard [aut] (<https://orcid.org/0000-0001-9818-479X>)
MaintainerMartijn Schuemie <schuemie@ohdsi.org>
LicenseApache License 2.0
Version3.0.0
URL https://ohdsi.github.io/EmpiricalCalibration/ https://github.com/OHDSI/EmpiricalCalibration
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("EmpiricalCalibration")

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EmpiricalCalibration documentation built on Sept. 28, 2021, 9:07 a.m.