Network Meta-Analysis Using Bayesian Methods


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Documentation for package ‘gemtc’ version 0.6-1

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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