Package index • RaCE.NMA

Model Estimation Function Primary function to estimate RaCE NMA models
`mcmc_raceNMA()`	Fit a Bayesian Rank-Clustered Estimation model for Network Meta-Analysis (RaCE-NMA) using multiple MCMC chains
Model Plotting and Assessment Functions Functions that allow for plotting results of RaCE NMA models or assessing MCMC chains.
`traceplot_mu()`	Create trace plots for the mu parameter in RaCE NMA models
`traceplot_K()`	Create trace plots for the K parameter in RaCE NMA models
`forestplot_muhat()`	Create posterior forest plots for relative treatment effect estimates from a standard or RaCE NMA study
`clusterplot_ranks()`	Create a posterior clustering matrix for the interventions based on RaCE NMA models
`cumulativeprobplot_ranks()`	Create a cumulative ranking plot in RaCE NMA models
`calculate_Rhat()`	Calculate Gelman Diagnostics for Fitted RaCE NMA Models
`calculate_SUCRA_MNBT()`	Calculate SUCRA and MNBT based on MCMC draws in NMA or RaCE-NMA models
Data Datasets for package demonstration and reproducibility
`wang_posterior`	Posterior relative treatment effects for non-baseline treatments based on Wang et. al (2022)
`toy_data`	Toy data of posterior relative treatment effects
Helper Functions Functions used during model-fitting that are not needed by the user, but are provided for completeness and reproducibility.
`sample_partition_independence()`	Partition sampling in Bayesian RaCE-NMA models (internal use only)
`sample_partition_correlation()`	Partition sampling in Bayesian RaCE-NMA models (internal use only)
`fit_raceNMA()`	Fit a Bayesian Rank-Clustered Estimation model for Network Meta-Analysis (RaCE-NMA). Recommended for internal use only; use mcmc_RCMVN instead.