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bayesmeta (version 2.3)

Bayesian Random-Effects Meta-Analysis

Description

A collection of functions allowing to derive the posterior distribution of the two parameters in a random-effects meta-analysis, and providing functionality to evaluate joint and marginal posterior probability distributions, predictive distributions, shrinkage effects, posterior predictive p-values, etc.

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Version

Install

install.packages('bayesmeta')

Monthly Downloads

1,279

Version

2.3

License

GPL (>= 2)

Homepage

https://gitlab.gwdg.de/croever/bayesmeta

Maintainer

Christian Roever

Last Published

October 11th, 2018

Functions in bayesmeta (2.3)

Fly counts example data

RhodesEtAlPrior

Heterogeneity priors for continuous outcomes (standardized mean differences) as proposed by Rhodes et al. (2015).

8-schools example data

Pediatric liver transplant example data

Half-logistic distribution.

Half-normal, half-Student-t and half-Cauchy distributions.

SidikJonkman2007

Postoperative complication odds example data

Generate summary plots for a bayesmeta object.

bayesmeta-package

Bayesian Random-Effects Meta-Analysis

Bayesian random-effects meta-analysis

Posterior predictive \(p\)-values

forestplot.bayesmeta

Generate a forest plot for a bayesmeta object (based on the forestplot package's plotting functions).

forest.bayesmeta

Generate a forest plot for a bayesmeta object (based on the metafor package's plotting functions).

GoralczykEtAl2011

Liver transplant example data

Aspirin after myocardial infarction example data

TurnerEtAlPrior

(Log-Normal) heterogeneity priors for binary outcomes as proposed by Turner et al. (2015).

JIA example data

SnedecorCochran

Artificial insemination of cows example data

The Lomax distribution.

Compute normal mixtures

The Rayleigh distribution.