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Provides a new class of Bayesian meta-analysis models that incorporates a model for internal and external validity bias. In this way, it is possible to combine studies of diverse quality and different types. For example, we can combine the results of randomized control trials (RCTs) with the results of observational studies (OS).
Version: | 2.2.3 |
Depends: | R (≥ 4.0.0) |
Imports: | rjags, R2jags, stats, graphics, ggplot2, ggExtra, MASS, grid, gridExtra, mcmcplots, bookdown, tidyr, kableExtra, GGally, qpdf |
Published: | 2024-12-05 |
DOI: | 10.32614/CRAN.package.jarbes |
Author: | Pablo Emilio Verde [aut, cre] |
Maintainer: | Pablo Emilio Verde <pabloemilio.verde at hhu.de> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
SystemRequirements: | JAGS (>= 4.3.0) (see http://mcmc-jags.sourceforge.net) |
Materials: | ChangeLog |
In views: | MetaAnalysis |
CRAN checks: | jarbes results |
Reference manual: | jarbes.pdf |
Package source: | jarbes_2.2.3.tar.gz |
Windows binaries: | r-devel: jarbes_2.2.3.zip, r-release: jarbes_2.2.3.zip, r-oldrel: jarbes_2.2.3.zip |
macOS binaries: | r-release (arm64): jarbes_2.2.3.tgz, r-oldrel (arm64): jarbes_2.2.3.tgz, r-release (x86_64): jarbes_2.2.3.tgz, r-oldrel (x86_64): jarbes_2.2.3.tgz |
Old sources: | jarbes archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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