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 |