Bayesian Meta-Analysis and Network Meta-Analysis

Documentation for package ‘metapack’ version 0.1.2

bayes.nmr	Fit Bayesian Network Meta-Regression Hierarchical Models Using Heavy-Tailed Multivariate Random Effects with Covariate-Dependent Variances
bayes.parobs	Fit Bayesian Inference for Multivariate Meta-Regression With a Partially Observed Within-Study Sample Covariance Matrix
cholesterol	26 double-blind, randomized, active, or placebo-controlled clinical trials on patients with primary hypercholesterolemia sponsored by Merck & Co., Inc., Kenilworth, NJ, USA.
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
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
TNM	Triglycerides Network Meta (TNM) data