# Bayesian Meta-Analysis and Network Meta-Analysis

## Documentation for package ‘metapack’ version 0.3

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

bayes_nmr | Fit Bayesian Network Meta-Regression Models
bayes_parobs | Fit Bayesian Inference for Meta-Regression
bmeta_analyse | bmeta_analyze supersedes the previous two functions: bayes_parobs, bayes_nmr
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'"
TNM | Triglycerides Network Meta (TNM) data