Bayesian Meta-Analysis and Network Meta-Analysis

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Documentation for package ‘metapack’ version 0.3

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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