R: Network Meta-Analysis Using Bayesian Methods

# Network Meta-Analysis Using Bayesian Methods

## Documentation for package ‘gemtc’ version 1.1-1

- DESCRIPTION file
- Package NEWS

## Help Pages

gemtc-package | GeMTC: Network meta-analysis in R
as.data.frame.mtc.relative.effect.table | Table of relative effects
as.mcmc.list.mtc.result | Running an 'mtc.model' using an MCMC sampler
atrialFibrillation | Prevention of stroke in atrial fibrillation patients
blobbogram | Plot a blobbogram (AKA forest plot)
blocker | Beta blockers to prevent mortality after myocardial infarction
certolizumab | Certolizumab Pegol (CZP) for Rheumatoid Arthritis
depression | Treatment response in major depression
dietfat | Effects of low-fat diets on mortality
forest | Plot a blobbogram (AKA forest plot)
forest.mtc.relative.effect.table | Table of relative effects
forest.mtc.result | Running an 'mtc.model' using an MCMC sampler
gemtc | GeMTC: Network meta-analysis in R
hfPrevention | Statins versus placebo in primary and secondary prevention of heart failure
ll.call | Call a likelihood/link-specific function
mtc | GeMTC: Network meta-analysis in R
mtc.anohe | Analysis of heterogeneity (ANOHE)
mtc.data.studyrow | Convert one-study-per-row datasets
mtc.deviance | Inspect residual deviance
mtc.devplot | Inspect residual deviance
mtc.hy.empirical.lor | Set priors for the heterogeneity parameter
mtc.hy.prior | Set priors for the heterogeneity parameter
mtc.levplot | Inspect residual deviance
mtc.model | Generate network meta-analysis models
mtc.network | Create an mtc.network
mtc.nodesplit | Node-splitting analysis of inconsistency
mtc.nodesplit.comparisons | Node-splitting analysis of inconsistency
mtc.result | Running an 'mtc.model' using an MCMC sampler
mtc.run | Running an 'mtc.model' using an MCMC sampler
parkinson | Mean off-time reduction in Parkinson's disease
parkinson_diff | Mean off-time reduction in Parkinson's disease
parkinson_shared | Mean off-time reduction in Parkinson's disease
plot.mtc.anohe | Analysis of heterogeneity (ANOHE)
plot.mtc.anohe.summary | Analysis of heterogeneity (ANOHE)
plot.mtc.deviance | Inspect residual deviance
plot.mtc.model | Generate network meta-analysis models
plot.mtc.network | Create an mtc.network
plot.mtc.nodesplit | Node-splitting analysis of inconsistency
plot.mtc.nodesplit.summary | Node-splitting analysis of inconsistency
plot.mtc.rank.probability | Calculating rank-probabilities
plot.mtc.result | Running an 'mtc.model' using an MCMC sampler
plotCovariateEffect | Plot treatment effects versus covariate values
print.mtc.anohe | Analysis of heterogeneity (ANOHE)
print.mtc.anohe.summary | Analysis of heterogeneity (ANOHE)
print.mtc.model | Generate network meta-analysis models
print.mtc.nodesplit | Node-splitting analysis of inconsistency
print.mtc.nodesplit.summary | Node-splitting analysis of inconsistency
print.mtc.rank.probability | Calculating rank-probabilities
print.mtc.relative.effect.table | Table of relative effects
print.mtc.result | Running an 'mtc.model' using an MCMC sampler
rank.probability | Calculating rank-probabilities
rank.quantiles | Calculating rank-probabilities
relative.effect | Calculating relative effects
relative.effect.table | Table of relative effects
smoking | Psychological treatments to aid smoking cessation
sucra | Calculating rank-probabilities
summary.mtc.anohe | Analysis of heterogeneity (ANOHE)
summary.mtc.model | Generate network meta-analysis models
summary.mtc.nodesplit | Node-splitting analysis of inconsistency
summary.mtc.result | Running an 'mtc.model' using an MCMC sampler
thrombolytic | Thrombolytic treatment after acute myocardial infarction