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.

Install the latest version of this package by entering the following in R:

`install.packages("bmeta")`

Author | Tao Ding, Gianluca Baio |

Date of publication | 2016-01-08 10:53:20 |

Maintainer | Gianluca Baio <gianluca@stats.ucl.ac.uk> |

License | GPL (>= 2) |

Version | 0.1.2 |

http://www.statistica.it/gianluca/bmeta, http://www.statistica.it/gianluca |

**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...

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.

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