R: Bayesian Network Meta-Analysis using 'JAGS'

# Bayesian Network Meta-Analysis using 'JAGS'

## Documentation for package ‘bnma’ version 1.6.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

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