Package: bnma 1.6.1

bnma: Bayesian Network Meta-Analysis using 'JAGS'

Network meta-analyses using Bayesian framework following Dias et al. (2013) <doi:10.1177/0272989X12458724>. Based on the data input, creates prior, model file, and initial values needed to run models in 'rjags'. Able to handle binomial, normal and multinomial arm-level data. Can handle multi-arm trials and includes methods to incorporate covariate and baseline risk effects. Includes standard diagnostics and visualization tools to evaluate the results.

Authors:Michael Seo [aut, cre], Christopher Schmid [aut]

bnma_1.6.1.tar.gz
bnma_1.6.1.zip(r-4.7)bnma_1.6.1.zip(r-4.6)bnma_1.6.1.zip(r-4.5)
bnma_1.6.1.tgz(r-4.6-any)bnma_1.6.1.tgz(r-4.5-any)
bnma_1.6.1.tar.gz(r-4.7-any)bnma_1.6.1.tar.gz(r-4.6-any)
bnma_1.6.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bnma/json (API)

# Install 'bnma' in R:

install.packages('bnma', repos = c('https://mikejseo.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mikejseo/bnma/issues

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC
c++– GNU Standard C++ Library v3

Datasets:

blocker - Beta blockers to prevent mortality after myocardial infarction
cardiovascular - Trials of low dose and high dose statins for cardiovascular disease vs. placebo
certolizumab - Trials of certolizumab pegol (CZP) for the treatment of rheumatoid arthritis in patients
parkinsons - Dopamine agonists as adjunct therapy in Parkinson's disease
parkinsons_contrast - Dopamine agonists as adjunct therapy in Parkinson's disease
smoking - Smoking cessation counseling programs
statins - Trials of statins for cholesterol lowering vs. placebo or usual care
thrombolytic - Thrombolytic drugs and percutaneous transluminal coronary angioplasty

On CRAN:

jags cpp

5.08 score 8 stars 1 packages 8 scripts 372 downloads 1 mentions 29 exports 24 dependencies

Last updated from:c7c327e257. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	146
source / vignettes	OK	319
linux-release-x86_64	OK	119
macos-release-arm64	OK	111
macos-oldrel-arm64	OK	88
windows-devel	OK	99
windows-release	OK	96
windows-oldrel	OK	103
wasm-release	OK	115

Exports:calculate.contrast.deviance calculate.deviance contrast.network.data contrast.network.deviance.plot contrast.network.leverage.plot contrast.network.run draw.network.graph network.autocorr.diag network.autocorr.plot network.covariate.plot network.cumrank.tx.plot network.data network.deviance.plot network.forest.plot network.gelman.diag network.gelman.plot network.inconsistency.plot network.leverage.plot network.rank.tx.plot network.run nodesplit.network.data nodesplit.network.run rank.tx relative.effects relative.effects.table sucra ume.network.data ume.network.run variance.tx.effects

Dependencies:cli coda cpp11 farver ggplot2 glue gtable igraph isoband labeling lattice lifecycle magrittr Matrix pkgconfig R6 RColorBrewer rjags rlang S7 scales vctrs viridisLite withr

Bayesian network meta analysis

Rendered frombnma.Rmdusingknitr::rmarkdown

Last update: 2024-02-11
Started: 2024-02-10

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
bnma: A package for network meta analysis using Bayesian methods	bnma-package
Beta blockers to prevent mortality after myocardial infarction	blocker
Find deviance statistics such as DIC and pD.	calculate.contrast.deviance
Find deviance statistics such as DIC and pD.	calculate.deviance
Trials of low dose and high dose statins for cardiovascular disease vs. placebo	cardiovascular
Trials of certolizumab pegol (CZP) for the treatment of rheumatoid arthritis in patients	certolizumab
Make a network object for contrast-level data containing data, priors, and a JAGS model file	contrast.network.data
Make a contrast network deviance plot	contrast.network.deviance.plot
Make a leverage plot	contrast.network.leverage.plot
Run the model using the network object	contrast.network.run
Draws network graph using igraph package	draw.network.graph
Generate autocorrelation diagnostics using coda package	network.autocorr.diag
Generate autocorrelation plot using coda package	network.autocorr.plot
Make a covariate plot	network.covariate.plot
Create a treatment cumulative rank plot	network.cumrank.tx.plot
Make a network object containing data, priors, and a JAGS model file	network.data
Make a deviance plot	network.deviance.plot
Draws forest plot	network.forest.plot
Use coda package to find Gelman-Rubin diagnostics	network.gelman.diag
Use coda package to plot Gelman-Rubin diagnostic plot	network.gelman.plot
Plotting comparison of posterior mean deviance in the consistency model and inconsistency model	network.inconsistency.plot
Make a leverage plot	network.leverage.plot
Create a treatment rank plot	network.rank.tx.plot
Run the model using the network object	network.run
Make a network object containing data, priors, and a JAGS model file	nodesplit.network.data
Run the model using the nodesplit network object	nodesplit.network.run
Dopamine agonists as adjunct therapy in Parkinson's disease	parkinsons
Dopamine agonists as adjunct therapy in Parkinson's disease	parkinsons_contrast
Plot traceplot and posterior density of the result using contrast data	plot.contrast.network.result
Plot traceplot and posterior density of the result	plot.network.result
Plot traceplot and posterior density of the result using contrast data	plot.ume.network.result
Create a treatment rank table	rank.tx
Find relative effects for base treatment and comparison treatments	relative.effects
Make a summary table for relative effects	relative.effects.table
Smoking cessation counseling programs	smoking
Trials of statins for cholesterol lowering vs. placebo or usual care	statins
Calculate SUCRA	sucra
Summarize result run by 'contrast.network.run'	summary.contrast.network.result
Summarize result run by 'network.run'	summary.network.result
Summarize result run by 'nodesplit.network.run'	summary.nodesplit.network.result
Summarize result run by 'ume.network.run'	summary.ume.network.result
Thrombolytic drugs and percutaneous transluminal coronary angioplasty	thrombolytic
Make a network object for the unrelated mean effects model (inconsistency model) containing data, priors, and a JAGS model file	ume.network.data
Run the model using the network object	ume.network.run
Calculate correlation matrix for multinomial heterogeneity parameter.	variance.tx.effects