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Function to create forest plots. Functions to use posterior samples from Bayesian bivariate meta-analysis model, Bayesian hierarchical summary receiver operating characteristic (HSROC) meta-analysis model or Bayesian latent class (LC) meta-analysis model to create Summary Receiver Operating Characteristic (SROC) plots using methods described by Harbord et al (2007)<doi:10.1093/biostatistics/kxl004>.
| Version: | 1.0.2.5 |
| Depends: | R (≥ 3.5.0) |
| Published: | 2021-10-15 |
| DOI: | 10.32614/CRAN.package.DTAplots |
| Author: | Ian Schiller [aut, cre], Nandini Dendukuri [ctb] |
| Maintainer: | Ian Schiller <ian.schiller at rimuhc.ca> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | NEWS |
| In views: | MetaAnalysis |
| CRAN checks: | DTAplots results |
| Reference manual: | DTAplots.pdf |
| Package source: | DTAplots_1.0.2.5.tar.gz |
| Windows binaries: | r-devel: DTAplots_1.0.2.5.zip, r-release: DTAplots_1.0.2.5.zip, r-oldrel: DTAplots_1.0.2.5.zip |
| macOS binaries: | r-release (arm64): DTAplots_1.0.2.5.tgz, r-oldrel (arm64): DTAplots_1.0.2.5.tgz, r-release (x86_64): DTAplots_1.0.2.5.tgz, r-oldrel (x86_64): DTAplots_1.0.2.5.tgz |
| Old sources: | DTAplots 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.