
Package index
-
balloon_plot() - Enhanced balloon plot
-
baseline_model() - The baseline model for binary outcome
-
bland_altman_plot() - The Bland-Altman plot
-
comp_clustering() - End-user-ready results for comparison dissimilarity and hierarchical clustering (Comparisons' comparability for transitivity evaluation)
-
covar_contribution_plot() - Visualising study percentage contributions against a covariate
-
data_preparation() - Prepare the dataset in the proper format for R2jags
-
dendro_heatmap() - Dendrogram with amalgamated heatmap (Comparisons' comparability for transitivity evaluation)
-
describe_network() - A function to describe the evidence base
-
distr_characteristics() - Visualising the distribution of characteristics (Comparisons' comparability for transitivity evaluation)
-
forestplot() - Comparator-specific forest plot for network meta-analysis
-
forestplot_juxtapose() - Forest plot of juxtaposing several network meta-analysis models
-
forestplot_metareg() - Comparator-specific forest plot for network meta-regression
-
gower_distance() - Weighted Gower's dissimilarity measure (Trials' comparability for transitivity evaluation)
-
heatmap_missing_dataset() - Heatmap of proportion of missing participants in the dataset
-
heatmap_missing_network() - Heatmap of proportion of missing participants in the network
-
heatmap_robustness() - Heatmap of robustness
-
heter_density_plot() - Visualising the density of two prior distributions for the heterogeneity parameter
-
heterogeneity_param_prior() - Determine the prior distribution for the heterogeneity parameter
-
improved_ume() - Detect the frail comparisons in multi-arm trials
-
inconsistency_variance_prior() - Function for the hyper-parameters of the prior distribution of the inconsistency variance (network meta-analysis with random inconsistency effects)
-
internal_measures_plot() - Internal measures for cluster validation (Comparisons' comparability for transitivity evaluation)
-
intervalplot_panel_ume() - A panel of interval plots for the unrelated mean effects model
-
kld_barplot() - Barplot for the Kullback-Leibler divergence measure (missingness scenarios)
-
kld_inconsistency() - Density plots of local inconsistency results and Kullback-Leibler divergence when 'rnmamod', 'netmeta' or 'gemtc' R packages are used
-
kld_inconsistency_user() - Density plots of local inconsistency results and Kullback-Leibler divergence (When dataset is created by the user)
-
kld_measure() - Function for the Kullback-Leibler Divergence of two normally distributed treatment effects for the same pairwise comparison
-
league_heatmap() - League heatmap for estimation
-
league_heatmap_pred() - League heatmap for prediction
-
league_table_absolute() - League table for relative and absolute effects
-
league_table_absolute_user() - League table for relative and absolute effects (user defined)
-
leverage_plot() - Leverage plot
-
mcmc_diagnostics() - Markov Chain Monte Carlo diagnostics
-
metareg_plot() - End-user-ready results for network meta-regression
-
miss_characteristics() - Visualising missing data in characteristics (Comparisons' comparability for transitivity evaluation)
-
missingness_param_prior() - Define the mean value of the normal distribution of the missingness parameter
-
netplot() - Network plot
-
nma.baker2009 - Pharmacological interventions for chronic obstructive pulmonary disease
-
nma.bottomley2011 - Pharmacological interventions for moderately severe scalp psoriasis
-
nma.dogliotti2014 - Oral antithrombotics for stroke episode
-
nma.fluoride.donegan2018 - Topical fluoride interventions for preventing dental caries
-
nma.liu2013 - Antidepressants in Parkinson's disease
-
nma.malaria.donegan2018 - Artemether, artesunate and quinine for severe malaria
-
nma.schwingshackl2014 - Training modalities for patients with type 2 diabetes
-
nma.stowe2011 - Antiparkinsonian interventions for later Parkinson's disease
-
nodesplit_plot() - End-user-ready results for the node-splitting approach
-
plot_study_dissimilarities() - Plot Gower's disimilarity values for each study (Transitivity evaluation)
-
pma.hetrick2012 - Paroxetine versus placebo for depressive disorders
-
pma.taylor2004 - Inositol versus glucose for depressive episode
-
prepare_model() - WinBUGS code for Bayesian pairwise or network meta-analysis and meta-regression
-
prepare_nodesplit() - WinBUGS code for the node-splitting approach
-
prepare_ume() - WinBUGS code for the unrelated mean effects model
-
rankosucra_plot() - Rankograms and SUCRA curves
-
rnmamod-packagernmamod - rnmamod: Bayesian Network Meta-analysis with Missing Participants
-
robustness_index() - Robustness index
-
robustness_index_user() - Robustness index when 'metafor' or 'netmeta' are used
-
run_metareg() - Perform Bayesian pairwise or network meta-regression
-
run_model() - Perform Bayesian pairwise or network meta-analysis
-
run_nodesplit() - Perform the node-splitting approach
-
run_sensitivity() - Perform sensitivity analysis for missing participant outcome data
-
run_series_meta() - Perform a series of Bayesian pairwise meta-analyses
-
run_ume() - Perform the unrelated mean effects model
-
scatterplot_sucra() - Scatterplot of SUCRA values
-
scatterplots_dev() - Deviance scatterplots
-
series_meta_plot() - End-user-ready results for a series of pairwise meta-analyses
-
study_perc_contrib() - Calculate study percentage contributions to summary treatment effects or regression coefficients
-
table_tau2_prior() - Predictive distributions for the between-study variance in a future meta-analysis on odds ratio or standardised mean difference
-
taylor_continuous() - Pattern-mixture model with Taylor series for continuous outcome
-
taylor_imor() - Pattern-mixture model with Taylor series for a binary outcome
-
ume_plot() - End-user-ready results for the unrelated mean effects model
-
unrelated_effects_plot() - End-user-ready results for unrelated trial effects model