TNM                     Triglycerides Network Meta (TNM) data
bayes_nmr               Fit Bayesian Network Meta-Regression Models
bayes_parobs            Fit Bayesian Inference for Meta-Regression
bmeta_analyze           bmeta_analyze supersedes the previous two
                        functions: bayes_parobs, bayes_nmr
cholesterol             26 double-blind, randomized, active, or
                        placebo-controlled clinical trials on patients
                        with primary hypercholesterolemia sponsored by
                        Merck & Co., Inc., Kenilworth, NJ, USA.
coef.bsynthesis         get the posterior mean of fixed-effect
                        coefficients
fitted.bayesnmr         get fitted values
fitted.bayesparobs      get fitted values
hpd                     get the highest posterior density (HPD)
                        interval
hpd.bayesnmr            get the highest posterior density (HPD)
                        interval
hpd.bayesparobs         get the highest posterior density (HPD)
                        interval or equal-tailed credible interval
metapack                metapack: a package for Bayesian meta-analysis
                        and network meta-analysis
model_comp              compute the model comparison measures: DIC,
                        LPML, or Pearson's residuals
model_comp.bayesnmr     get compute the model comparison measures
model_comp.bayesparobs
                        compute the model comparison measures
ns                      helper function encoding trial sample sizes in
                        formulas
plot.bayesnmr           get goodness of fit
plot.bayesparobs        get goodness of fit
plot.sucra              plot the surface under the cumulative ranking
                        curve (SUCRA)
print.bayesnmr          Print results
print.bayesparobs       Print results
sucra                   get surface under the cumulative ranking curve
                        (SUCRA)
sucra.bayesnmr          get surface under the cumulative ranking curve
                        (SUCRA)
summary.bayesnmr        'summary' method for class "'bayesnmr'"
summary.bayesparobs     'summary' method for class "'bayesparobs'"
