Package: metaBMA
Type: Package
Date: 2023-09-12
Title: Bayesian Model Averaging for Random and Fixed Effects
        Meta-Analysis
Version: 0.6.9
Authors@R: c(person(given = "Daniel W.",  
                    family = "Heck", 
                    email="daniel.heck@uni-marburg.de", 
                    role=c("aut","cre"),
                    comment = c(ORCID = "0000-0002-6302-9252")),
             person(given = "Quentin F.",  
                    family = "Gronau", 
                    email="quentingronau@web.de", 
                    role = "ctb"),
             person(given = "Eric-Jan",  
                    family = "Wagenmakers", 
                    email="ej.wagenmakers@gmail.com", 
                    role = "ctb"),
             person(given = "Indrajeet", 
                    family = "Patil", 
                    email = "patilindrajeet.science@gmail.com", 
                    role = "ctb",
                    comment = c(ORCID = "0000-0003-1995-6531")))
Description: Computes the posterior model probabilities for standard 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, <doi:10.1080/23743603.2017.1326760>). The user can define 
    a wide range of non-informative or informative priors for the mean effect size 
    and the heterogeneity coefficient. Moreover, using pre-compiled Stan models, 
    meta-analysis with continuous and discrete moderators with Jeffreys-Zellner-Siow (JZS) 
    priors can be fitted and tested. This allows to compute Bayes factors and 
    perform Bayesian model averaging across random- and fixed-effects meta-analysis 
    with and without moderators. For a primer on Bayesian model-averaged meta-analysis, 
    see Gronau, Heck, Berkhout, Haaf, & Wagenmakers (2021, <doi:10.1177/25152459211031256>).
Depends: R (>= 4.0.0), Rcpp (>= 1.0.0), methods
Imports: bridgesampling, coda, LaplacesDemon, logspline, mvtnorm,
        RcppParallel (>= 5.0.1), rstan (>= 2.26.0), rstantools (>=
        2.3.0)
Suggests: testthat, knitr, rmarkdown, spelling
LinkingTo: BH (>= 1.78.0), Rcpp (>= 1.0.0), RcppEigen (>= 0.3.3.9.1),
        RcppParallel (>= 5.0.1), rstan (>= 2.26.0), StanHeaders (>=
        2.26.0)
VignetteBuilder: knitr
URL: https://github.com/danheck/metaBMA,
        https://danheck.github.io/metaBMA/
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
SystemRequirements: GNU make
Biarch: true
Language: en-US
RoxygenNote: 7.2.3
Packaged: 2023-09-12 21:04:25 UTC; daniel
Author: Daniel W. Heck [aut, cre] (<https://orcid.org/0000-0002-6302-9252>),
  Quentin F. Gronau [ctb],
  Eric-Jan Wagenmakers [ctb],
  Indrajeet Patil [ctb] (<https://orcid.org/0000-0003-1995-6531>)
Maintainer: Daniel W. Heck <daniel.heck@uni-marburg.de>
Repository: CRAN
Date/Publication: 2023-09-13 07:20:02 UTC
Built: R 4.4.3; x86_64-w64-mingw32; 2025-11-12 04:49:47 UTC; windows
Archs: x64
