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]

crossnma_1.3.0.tar.gz
crossnma_1.3.0.tar.gz(r-4.5-noble)crossnma_1.3.0.tar.gz(r-4.4-noble)
crossnma_1.3.0.tgz(r-4.4-emscripten)crossnma_1.3.0.tgz(r-4.3-emscripten)
crossnma.pdf |crossnma.html
crossnma/json (API)
NEWS

# Install 'crossnma' in R:
install.packages('crossnma', repos = c('https://cran.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.

jagscpp

2.00 score 289 downloads 3 exports 66 dependencies

Last updated 10 days agofrom:8355877ba0. Checks:OK: 1 WARNING: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 28 2024
R-4.5-linuxWARNINGNov 28 2024

Exports:crossnmacrossnma.modelleague

Dependencies:abindbitbit64bootclicliprcodacolorspaceCompQuadFormcpp11crayondplyrfansifarvergenericsggplot2gluegtablehmsisobandlabelinglatticelifecyclelme4magicmagrittrMASSmathjaxrMatrixmetametadatmetaformgcvminqamunsellnetmetanlmenloptrnumDerivpbapplypillarpkgconfigplyrprettyunitsprogresspurrrR6RColorBrewerRcppRcppEigenreadrrjagsrlangscalesstringistringrtibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithrxml2

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

Rendered fromcrossnma.Rmdusingknitr::rmarkdownon Nov 28 2024.

Last update: 2023-09-18
Started: 2022-04-15