Bayesian Meta-Analysis and Network Meta-Analysis


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Documentation for package ‘metapack’ version 0.1.2

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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