Provides a new class of Bayesian meta-analysis models that we called "The Hierarchical Meta-Regression" (HMR). The aim of HMR is to incorporate into the meta-analysis, the data collection process, which results in a model for the internal and external validity bias. In this way, it is possible to combine studies of different types. For example, we can combine the results of randomized control trials (RCTs) with the results of observational studies (OS). The statistical methods and their applications are described in Verde (2019) <doi:10.1002/bimj.201700266> and in Verde (2017) <doi:10.5772/intechopen.70231>.
| Version: | 1.7.2 |
| Depends: | R (≥ 3.4.0) |
| Imports: | rjags (≥ 3.4.0), R2jags (≥ 0.04-03), stats, graphics, ggplot2, ggExtra, MASS, grid, gridExtra, mcmcplots |
| Published: | 2019-03-11 |
| 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 (>= 3.4.0) (see http://mcmc-jags.sourceforge.net) |
| Materials: | ChangeLog |
| In views: | MetaAnalysis |
| CRAN checks: | jarbes results |
| Reference manual: | jarbes.pdf |
| Package source: | jarbes_1.7.2.tar.gz |
| Windows binaries: | r-devel: jarbes_1.7.2.zip, r-release: jarbes_1.7.2.zip, r-oldrel: jarbes_1.7.2.zip |
| macOS binaries: | r-release: jarbes_1.7.2.tgz, r-oldrel: jarbes_1.7.2.tgz |
| Old sources: | jarbes archive |
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