Provides a collection of functions for conducting meta-analyses under Bayesian context in R. The package includes functions for computing various effect size or outcome measures (e.g. odds ratios, mean difference and incidence rate ratio) for different types of data based on MCMC simulations. Users are allowed to fit fixed- and random-effects models with different priors to the data. Meta-regression can be carried out if effects of additional covariates are observed. Furthermore, the package provides functions for creating posterior distribution plots and forest plot to display main model output. Traceplots and some other diagnostic plots are also available for assessing model fit and performance.
|Author||Tao Ding, Gianluca Baio|
|Date of publication||2016-01-08 10:53:20|
|Maintainer||Gianluca Baio <firstname.lastname@example.org>|
|License||GPL (>= 2)|
acf.plot: Autocorrelation function plot
bmeta: Bayesian Meta Analysis/Meta-regression
bmeta-package: bmeta: A Bayesian Meta-Analysis Package for R
diag.plot: Diagnostic plot to examine model fit
forest.plot: Function to create forest plot
funnel.plot: Funnel plot to examine publication bias
posterior.plot: Posterior distribution plots for summary estimates and...
print.bmeta: Print method for 'bmeta' objects
traceplot.bmeta: Traceplot to assess convergence
writeModel: A function to write a text file encoding the modelling...