CRAN

metaBMA 0.3.9

Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis

Released Aug 4, 2017 by Daniel W. Heck

This package can be loaded by Renjin but 7 out 14 tests failed.

Dependencies

LaplacesDemon 16.1.0 runjags 2.0.4-2 coda 0.19-1 mvtnorm 1.0-8 logspline 2.1.9

Computes the posterior model probabilities for four meta-analysis models (null model vs. alternative model assuming either fixed- or random-effects, respectively). These posterior probabilities are used to estimate the overall mean effect size as the weighted average of the mean effect size estimates of the random- and fixed-effect model as proposed by Gronau, Van Erp, Heck, Cesario, Jonas, & Wagenmakers (2017, ). The user can define a wide range of noninformative or informative priors for the mean effect size and the heterogeneity coefficient. Funding for this research was provided by the Berkeley Initiative for Transparency in the Social Sciences, a program of the Center for Effective Global Action (CEGA), with support from the Laura and John Arnold Foundation.

Installation

Maven

This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

<dependencies>
  <dependency>
    <groupId>org.renjin.cran</groupId>
    <artifactId>metaBMA</artifactId>
    <version>0.3.9-b12</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

View build log

Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:metaBMA')

Test Results

This package was last tested against Renjin 0.9.2644 on Jun 2, 2018.

Source

R

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Release History