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Network meta-analysis and network meta-regression models for aggregate data, individual patient data, and mixtures of both individual and aggregate data using multilevel network meta-regression as described by Phillippo et al. (2020) <doi:10.1111/rssa.12579>. Models are estimated in a Bayesian framework using 'Stan'.
Version: | 0.7.2 |
Depends: | R (≥ 3.4.0) |
Imports: | methods, stats, graphics, survival, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), rstantools (≥ 2.0.0), Rdpack (≥ 0.7), tibble (≥ 2.1.3), dplyr (≥ 1.0.0), rlang, purrr, forcats, glue, randtoolbox, copula, tidyr (≥ 1.0.0), stringr, Matrix, igraph, ggraph, ggplot2 (≥ 3.3.0), ggdist (≥ 2.1.1), truncdist, bayesplot |
LinkingTo: | BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), StanHeaders (≥ 2.32.9) |
Suggests: | testthat (≥ 2.1.0), vdiffr, withr, knitr, rmarkdown, parallel, R.rsp, rprojroot, loo (≥ 2.0.0), logitnorm, crayon, tidygraph, pkgdown, splines2 (≥ 0.5.0), flexsurv, rstpm2 |
Published: | 2024-09-16 |
DOI: | 10.32614/CRAN.package.multinma |
Author: | David M. Phillippo [aut, cre] |
Maintainer: | David M. Phillippo <david.phillippo at bristol.ac.uk> |
BugReports: | https://github.com/dmphillippo/multinma/issues |
License: | GPL-3 |
URL: | https://dmphillippo.github.io/multinma/, https://github.com/dmphillippo/multinma |
NeedsCompilation: | yes |
SystemRequirements: | GNU make |
Citation: | multinma citation info |
Materials: | README NEWS |
In views: | MetaAnalysis |
CRAN checks: | multinma results |
Package source: | multinma_0.7.2.tar.gz |
Windows binaries: | r-devel: multinma_0.7.2.zip, r-release: multinma_0.7.2.zip, r-oldrel: multinma_0.7.2.zip |
macOS binaries: | r-release (arm64): multinma_0.7.2.tgz, r-oldrel (arm64): multinma_0.7.2.tgz, r-release (x86_64): multinma_0.7.2.tgz, r-oldrel (x86_64): multinma_0.7.2.tgz |
Old sources: | multinma 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.