EvidenceSynthesis: Synthesizing Causal Evidence in a Distributed Research Network

Routines for combining causal effect estimates and study diagnostics across multiple data sites in a distributed study, without sharing patient-level data. Allows for normal and non-normal approximations of the data-site likelihood of the effect parameter.

Version: 0.2.3
Depends: survival, R (≥ 3.5.0)
Imports: ggplot2, gridExtra, meta, EmpiricalCalibration, rJava, BeastJar, Cyclops (≥ 3.1.0), HDInterval, coda, rlang, methods
Suggests: knitr, rmarkdown, testthat, sn
Published: 2021-01-29
Author: Martijn Schuemie [aut, cre], Marc A. Suchard [aut], Observational Health Data Science and Informatics [cph]
Maintainer: Martijn Schuemie <schuemie at ohdsi.org>
BugReports: https://github.com/OHDSI/EvidenceSynthesis/issues
License: Apache License 2.0
URL: https://ohdsi.github.io/EvidenceSynthesis/, https://github.com/OHDSI/EvidenceSynthesis
NeedsCompilation: no
SystemRequirements: Java version 8 or higher (https://www.java.com/)
Materials: README NEWS
CRAN checks: EvidenceSynthesis results


Reference manual: EvidenceSynthesis.pdf
Vignettes: Effect estimate using non-normal likelihood approximations
Package source: EvidenceSynthesis_0.2.3.tar.gz
Windows binaries: r-devel: EvidenceSynthesis_0.2.3.zip, r-release: EvidenceSynthesis_0.2.3.zip, r-oldrel: EvidenceSynthesis_0.2.3.zip
macOS binaries: r-release: EvidenceSynthesis_0.2.3.tgz, r-oldrel: EvidenceSynthesis_0.2.3.tgz
Old sources: EvidenceSynthesis archive


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