Bayesian Meta-Analysis and Network Meta-Analysis


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Documentation for package ‘metapack’ version 0.1.5

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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.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
TNM Triglycerides Network Meta (TNM) data