gemtc-package | GeMTC: Network meta-analysis in R |
as.mcmc.list.mtc.result | Running an 'mtc.model' using an MCMC sampler |
blobbogram | Plot a blobbogram (AKA forest plot) |
forest | Calculating relative effects |
forest.mtc.result | Running an 'mtc.model' using an MCMC sampler |
forest.mtc.results | Calculating relative effects |
gemtc | GeMTC: Network meta-analysis in R |
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.hy.empirical.lor | Set priors for the heterogeneity parameter |
mtc.hy.prior | Set priors for the heterogeneity parameter |
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.run | Running an 'mtc.model' using an MCMC sampler |
plot.mtc.anohe | Analysis of heterogeneity (ANOHE) |
plot.mtc.anohe.summary | Analysis of heterogeneity (ANOHE) |
plot.mtc.model | Generate network meta-analysis models |
plot.mtc.nodesplit | Node-splitting analysis of inconsistency |
plot.mtc.nodesplit.summary | Node-splitting analysis of inconsistency |
plot.mtc.result | Running an 'mtc.model' using an MCMC sampler |
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.result | Running an 'mtc.model' using an MCMC sampler |
rank.probability | Calculating rank-probabilities |
read.mtc.network | Create an mtc.network |
relative.effect | Calculating relative effects |
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 |
write.mtc.network | Create an mtc.network |