Package index • metainsight

All functions

baseline_compare(): Compare treatment pairs
baseline_deviance(): Produce deviance plots for baseline risk models
baseline_forest(): Produce a forest plot for baseline risk models
baseline_model(): Fit a baseline risk regression model
baseline_regression(): Baseline regression data
baseline_summary(): Summarise baseline risk
bayes_compare() covariate_compare(): Compare treatment pairs
bayes_details() covariate_details() baseline_details(): Summarise a Bayesian model
bayes_deviance() covariate_deviance(): Produce deviance plots
bayes_forest() covariate_forest(): Bayesian forest plot
bayes_mcmc() covariate_mcmc() baseline_mcmc(): Markov chain Monte Carlo plots
bayes_model(): Fit a Bayesian model
bayes_nodesplit(): Fit a Bayesian nodesplitting model
bayes_nodesplit_plot(): Bayesian nodesplitting forest plot
bayes_ranking() baseline_ranking() covariate_ranking(): Treatment rankings
bayes_results() covariate_results() baseline_results(): Summarise a Bayesian model
covariate_model(): Fit a covariate regression model
covariate_regression(): Covariate regression data
covariate_summary(): Summarise covariate data
density_plots(): Creates posterior density plots of MCMC samples.
dic_table(): Create a summary table of deviance information criterion stats for Bayesian models
export_cinema(): export_cinema
freq_compare(): Compare treatments for frequentist models
freq_forest(): Produce a frequentist forest plot
freq_inconsistency(): Inconsistency tables for frequentist models
freq_summary(): Summary forest plot matrix
gelman_plots(): Creates Gelman plots for a gemtc or bnma model.
make_netconnect(): Creates network connectivity info displayed under network plots
metainsight-package metainsight: metainsight: A flexible platform for meta-analysis
metaregression_plot(): Produce a meta-regression plot
network_structure(): Calculate edge.weights for network
ranking_plot(): Treatment ranking plots
ranking_table(): Ranking probability table
run_metainsight(): Run "metainsight" Application
setup_configure(): Configure the analysis
setup_configure_table(): Summarise the analysis configuration
setup_exclude(): Takes the configured data, removes any excluded studies and returns subsets of the data to be passed to other functions.
setup_exclude_plot(): Produce an version of the summary_study() plot for use in the interface for excluding studies. Inside the app this is interactive, but it can also be rendered for non-interactive use.
setup_load(): Load data
setup_upgrade(): Upgrade old data formats
summary_char(): Characterise the data
summary_network(): Produce a plot of the network using netmeta::netgraph()
summary_study(): Produce a forest plot of pairwise comparisons, grouped by treatment pairs. If risk of bias data was loaded these are also included.
trace_plots(): Creates trace plots of MCMC samples.
write_plot(): Write plots to a file