Package: crossnma 1.3.0

Guido Schwarzer

crossnma: Cross-Design & Cross-Format Network Meta-Analysis and Regression

Network meta-analysis and meta-regression (allows including up to three covariates) for individual participant data, aggregate data, and mixtures of both formats using the three-level hierarchical model. Each format can come from randomized controlled trials or non-randomized studies or mixtures of both. Estimates are generated in a Bayesian framework using JAGS. The implemented models are described by Hamza et al. 2023 <doi:10.1002/jrsm.1619>.

Authors:Tasnim Hamza [aut], Guido Schwarzer [aut, cre], Georgia Salanti [aut]

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NEWS

# Install 'crossnma' in R:
install.packages('crossnma', repos = c('https://htx-r.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/htx-r/crossnma/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • ipddata - Simulated individual participant dataset.
  • stddata - Simulated aggregate dataset.

On CRAN:

jagscpp

4.29 score 1 stars 13 scripts 364 downloads 3 exports 70 dependencies

Last updated 2 months agofrom:7fac52add8. Checks:4 OK, 4 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 27 2025
R-4.5-winOKJan 27 2025
R-4.5-macOKJan 27 2025
R-4.5-linuxOKJan 27 2025
R-4.4-winNOTEJan 27 2025
R-4.4-macNOTEJan 27 2025
R-4.3-winNOTEJan 27 2025
R-4.3-macNOTEJan 27 2025

Exports:crossnmacrossnma.modelleague

Dependencies:abindbitbit64bootclicliprcodacolorspaceCompQuadFormcpp11crayondplyrfansifarvergenericsggplot2gluegtablehmsisobandlabelinglatticelifecyclelme4magicmagrittrMASSmathjaxrMatrixmetametadatmetaformgcvminqamunsellmvtnormnetmetanlmenloptrnumDerivpbapplypillarpkgconfigplyrprettyunitsprogresspurrrR6rbibutilsRColorBrewerRcppRcppEigenRdpackreadrreformulasrjagsrlangscalesstringistringrtibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithrxml2

crossnma: Cross-Design & Cross-Format Network Meta-Analysis and Regression

Rendered fromcrossnma.Rmdusingknitr::rmarkdownon Jan 27 2025.

Last update: 2023-09-14
Started: 2021-11-30