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metapack (version 0.3)

Bayesian Meta-Analysis and Network Meta-Analysis

Description

Contains functions performing Bayesian inference for meta-analytic and network meta-analytic models through Markov chain Monte Carlo algorithm. Currently, the package implements Hui Yao, Sungduk Kim, Ming-Hui Chen, Joseph G. Ibrahim, Arvind K. Shah, and Jianxin Lin (2015) and Hao Li, Daeyoung Lim, Ming-Hui Chen, Joseph G. Ibrahim, Sungduk Kim, Arvind K. Shah, Jianxin Lin (2021) . For maximal computational efficiency, the Markov chain Monte Carlo samplers for each model, written in C++, are fine-tuned. This software has been developed under the auspices of the National Institutes of Health and Merck & Co., Inc., Kenilworth, NJ, USA.

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Version

Install

install.packages('metapack')

Monthly Downloads

254

Version

0.3

License

GPL (>= 3)

Maintainer

Daeyoung Lim

Last Published

January 24th, 2024

Functions in metapack (0.3)

bayes_nmr

Fit Bayesian Network Meta-Regression Models
hpd

get the highest posterior density (HPD) interval
fitted.bayesnmr

get fitted values
model_comp.bayesparobs

compute the model comparison measures
model_comp

compute the model comparison measures: DIC, LPML, or Pearson's residuals
ns

helper function encoding trial sample sizes in formulas
print.bayesparobs

Print results
hpd.bayesnmr

get the highest posterior density (HPD) interval
fitted.bayesparobs

get fitted values
model_comp.bayesnmr

get compute the model comparison measures
hpd.bayesparobs

get the highest posterior density (HPD) interval or equal-tailed credible interval
sucra

get surface under the cumulative ranking curve (SUCRA)
metapack

metapack: a package for Bayesian meta-analysis and network meta-analysis
sucra.bayesnmr

get surface under the cumulative ranking curve (SUCRA)
bayes_parobs

Fit Bayesian Inference for Meta-Regression
summary.bayesnmr

`summary` method for class "`bayesnmr`"
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.
plot.bayesnmr

get goodness of fit
coef.bsynthesis

get the posterior mean of fixed-effect coefficients
plot.bayesparobs

get goodness of fit
plot.sucra

plot the surface under the cumulative ranking curve (SUCRA)
print.bayesnmr

Print results
summary.bayesparobs

summary method for class "bayesparobs"
TNM

Triglycerides Network Meta (TNM) data