Package: metaBMA 0.6.9
metaBMA: Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis
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>).
Authors:
metaBMA_0.6.9.tar.gz
metaBMA_0.6.9.zip(r-4.5)metaBMA_0.6.9.zip(r-4.4)metaBMA_0.6.9.zip(r-4.3)
metaBMA_0.6.9.tgz(r-4.4-x86_64)metaBMA_0.6.9.tgz(r-4.4-arm64)metaBMA_0.6.9.tgz(r-4.3-x86_64)metaBMA_0.6.9.tgz(r-4.3-arm64)
metaBMA_0.6.9.tar.gz(r-4.5-noble)metaBMA_0.6.9.tar.gz(r-4.4-noble)
metaBMA.pdf |metaBMA.html✨
metaBMA/json (API)
NEWS
# Install 'metaBMA' in R: |
install.packages('metaBMA', repos = c('https://danheck.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/danheck/metabma/issues
- facial_feedback - Data Set: Facial Feedback
- power_pose - Data Set: Power Pose Effect
- power_pose_unfamiliar - Data Set: Power Pose Effect
- towels - Data Set: Reuse of Towels in Hotels
bayesbayes-factorbayesian-inferenceevidence-synthesismeta-analysismodel-averagingstan
Last updated 9 months agofrom:5c8ca4d4d2. Checks:OK: 2 NOTE: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 26 2024 |
R-4.5-win-x86_64 | NOTE | Oct 26 2024 |
R-4.5-linux-x86_64 | OK | Oct 26 2024 |
R-4.4-win-x86_64 | NOTE | Oct 26 2024 |
R-4.4-mac-x86_64 | NOTE | Oct 26 2024 |
R-4.4-mac-aarch64 | NOTE | Oct 26 2024 |
R-4.3-win-x86_64 | NOTE | Oct 26 2024 |
R-4.3-mac-x86_64 | NOTE | Oct 26 2024 |
R-4.3-mac-aarch64 | NOTE | Oct 26 2024 |
Exports:bmainclusionmeta_bmameta_defaultmeta_fixedmeta_orderedmeta_randommeta_sensitivityplot_defaultplot_forestplot_posteriorpredicted_bfpriortransform_es
Dependencies:abindbackportsBHbridgesamplingBrobdingnagcallrcheckmateclicodacolorspacedescdistributionalfansifarvergenericsggplot2gluegridExtragtableinlineisobandlabelingLaplacesDemonlatticelifecyclelogsplineloomagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeadersstringistringrtensorAtibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
metaBMA: Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis | metaBMA-package metaBMA |
Bayesian Model Averaging | bma |
Data Set: Facial Feedback | facial_feedback |
Inclusion Bayes Factor | inclusion |
Model Averaging for Meta-Analysis | meta_bma |
Defaults for Model Averaging in Meta-Analysis | meta_default |
Bayesian Fixed-Effects Meta-Analysis | meta_fixed |
Meta-Analysis with Order-Constrained Study Effects | meta_ordered |
Bayesian Random-Effects Meta-Analysis | meta_random |
Sensitivity Analysis for Bayesian Meta-Analysis | meta_sensitivity |
Plot Default Priors | plot_default |
Forest Plot for Meta-Analysis | plot_forest |
Plot Posterior Distribution | plot_posterior |
Plot Predicted Bayes Factors | plot.meta_pred |
Plot Sensitivity Analysis for Meta-Analysis | plot.meta_sensitivity |
Plot Prior Distribution | plot.prior |
Data Set: Power Pose Effect | power_pose power_pose_unfamiliar |
Predicted Bayes Factors for a New Study | predicted_bf |
Prior Distribution | prior |
Data Set: Reuse of Towels in Hotels | towels |
Transformation of Effect Sizes | transform_es |