Network Meta-Analysis Using Bayesian Methods
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Documentation for package ‘gemtc’ version 1.0-2
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 |