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.bayes.parobs     get fitted values
fitted.bayesnmr         get fitted values
hpd                     get the highest posterior density (HPD)
                        interval
hpd.bayes.parobs        get the highest posterior density (HPD)
                        interval or equal-tailed credible interval
hpd.bayesnmr            get the highest posterior density (HPD)
                        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.bayes.parobs
                        compute the model comparison measures
model.comp.bayesnmr     get compute the model comparison measures
ns                      helper function encoding trial sample sizes in
                        formulas
plot.bayes.parobs       get goodness of fit
plot.bayesnmr           get goodness of fit
plot.sucra              plot the surface under the cumulative ranking
                        curve (SUCRA)
print.bayes.parobs      Print results
print.bayesnmr          Print results
sucra                   get surface under the cumulative ranking curve
                        (SUCRA)
sucra.bayesnmr          get surface under the cumulative ranking curve
                        (SUCRA)
summary.bayes.parobs    'summary' method for class "'bayes.parobs'"
summary.bayesnmr        Summarize results
