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Bayesian component model-based network meta-analysis for treatment combinations with explicit component dose-response and dose-dependent interaction surfaces. The main interface fits single-timepoint arm-level networks with continuous or binary outcomes, any number of components, additive, bilinear, or saturating pairwise interactions, study-level random effects, and prediction at unobserved dose combinations. A stage-one longitudinal interface fits a two-component exponential time-course model with a bilinear interaction on the asymptote. Estimation uses 'Stan' through 'cmdstanr' or 'rstan'. Methods are described in Welton et al. (2009) <doi:10.1093/aje/kwp014>, Mawdsley et al. (2016) <doi:10.1002/psp4.12091>, Wicha et al. (2017) <doi:10.1038/s41467-017-01929-y>, and Pedder et al. (2019) <doi:10.1002/jrsm.1351>.
| Version: | 0.2.1 |
| Depends: | R (≥ 4.1.0) |
| Imports: | posterior, stats, graphics, grDevices, utils |
| Suggests: | cmdstanr, rstan, testthat (≥ 3.0.0), knitr, rmarkdown, loo |
| Published: | 2026-07-22 |
| DOI: | 10.32614/CRAN.package.cdtmbnma |
| Author: | Tyler Pitre [aut, cre] |
| Maintainer: | Tyler Pitre <pitretmed at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| SystemRequirements: | A working Stan backend through cmdstanr/CmdStan or rstan. |
| Additional_repositories: | https://stan-dev.r-universe.dev |
| Citation: | cdtmbnma citation info |
| Materials: | README, NEWS |
| CRAN checks: | cdtmbnma results |
| Reference manual: | cdtmbnma.html , cdtmbnma.pdf |
| Vignettes: |
Component-dose network meta-analysis with dose-dependent interactions (source, R code) |
| Package source: | cdtmbnma_0.2.1.tar.gz |
| Windows binaries: | r-devel: cdtmbnma_0.2.1.zip, r-release: cdtmbnma_0.2.1.zip, r-oldrel: cdtmbnma_0.2.1.zip |
| macOS binaries: | r-release (arm64): cdtmbnma_0.2.1.tgz, r-oldrel (arm64): cdtmbnma_0.2.1.tgz, r-release (x86_64): cdtmbnma_0.2.1.tgz, r-oldrel (x86_64): cdtmbnma_0.2.1.tgz |
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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.