Package: ra4bayesmeta 1.0-8

ra4bayesmeta: Reference Analysis for Bayesian Meta-Analysis

Functionality for performing a principled reference analysis in the Bayesian normal-normal hierarchical model used for Bayesian meta-analysis, as described in Ott, Plummer and Roos (2021) <doi:10.1002/sim.9076>. Computes a reference posterior, induced by a minimally informative improper reference prior for the between-study (heterogeneity) standard deviation. Determines additional proper anti-conservative (and conservative) prior benchmarks. Includes functions for reference analyses at both the posterior and the prior level, which, given the data, quantify the informativeness of a heterogeneity prior of interest relative to the minimally informative reference prior and the proper prior benchmarks. The functions operate on data sets which are compatible with the 'bayesmeta' package.

Authors:Manuela Ott [aut, cre], Malgorzata Roos [aut]

ra4bayesmeta_1.0-8.tar.gz
ra4bayesmeta_1.0-8.zip(r-4.5)ra4bayesmeta_1.0-8.zip(r-4.4)ra4bayesmeta_1.0-8.zip(r-4.3)
ra4bayesmeta_1.0-8.tgz(r-4.4-any)ra4bayesmeta_1.0-8.tgz(r-4.3-any)
ra4bayesmeta_1.0-8.tar.gz(r-4.5-noble)ra4bayesmeta_1.0-8.tar.gz(r-4.4-noble)
ra4bayesmeta_1.0-8.tgz(r-4.4-emscripten)ra4bayesmeta_1.0-8.tgz(r-4.3-emscripten)
ra4bayesmeta.pdf |ra4bayesmeta.html
ra4bayesmeta/json (API)

# Install 'ra4bayesmeta' in R:
install.packages('ra4bayesmeta', repos = c('https://manuelaott.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • aa - Auricular acupuncture data
  • aom - Acute otitis media data
  • rti - Respiratory tract infections data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 136 downloads 22 exports 14 dependencies

Last updated 1 years agofrom:574555b77f. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winNOTEOct 30 2024
R-4.5-linuxNOTEOct 30 2024
R-4.4-winNOTEOct 30 2024
R-4.4-macNOTEOct 30 2024
R-4.3-winOKOct 30 2024
R-4.3-macOKOct 30 2024

Exports:cal_h_distdsgcdsigcfit_models_RAfit_models_RA_5bmHH_fitsH_normalm_inf_sgcM_inf_sigcm_j_sgcM_j_sigcplot_RAplot_RA_5bmplot_RA_fitspost_mu_fepost_RApost_RA_3bmpost_RA_fitspri_RA_5bmpri_RA_fitssigma_ref

Dependencies:abindbackportsbayesmetacheckmateforestplotlatticemathjaxrMatrixmetadatmetaformvtnormnlmenumDerivpbapply

Readme and manuals

Help Manual

Help pageTopics
Reference Analysis for Bayesian Meta-Analysisra4bayesmeta-package
Auricular acupuncture dataaa
Acute otitis media dataaom
Calibration of the Hellinger distancecal_h_dist
Density function of the square-root generalized conventional (SGC) benchmark priordsgc
Density function of the square-root inverse generalized conventional (SIGC) benchmark priordsigc
Model fitting for reference analysis using 2 benchmarks: Posterior inference for benchmark and actual heterogeneity priorsfit_models_RA
Model fitting for reference analysis using 5 benchmarks: Posterior inference for benchmark and actual heterogeneity priorsfit_models_RA_5bm
Hellinger distance between two probability densitiesH
Hellinger distance between marignal posterior densities of two bayesmeta fitsH_fits
Approximate moment-based Hellinger distance computation between two probability densitiesH_normal
Optimization function for the SGC(m) prior: Adjust the prior to a target relative latent model complexity (RLMC)m_inf_sgc
Optimization function for the SIGC(M) prior: Adjust the prior to a target relative latent model complexity (RLMC)M_inf_sigc
Optimization function for the SGC(m) prior: Approximate Jeffreys reference posteriorm_j_sgc
Optimization function for the SIGC(m) prior: Approximate Jeffreys reference posteriorM_j_sigc
Reference analysis plot based on a data frame using 2 benchmarks: Plot heterogeneity benchmark priors and the corresponding marginal posteriorsplot_RA
Reference analysis plot based on a data frame using 5 benchmarks: Plot heterogeneity benchmark priors and the corresponding marginal posteriorsplot_RA_5bm
Reference analysis plot based on bayesmeta fits: Plot heterogeneity benchmark priors and the corresponding marginal posteriorsplot_RA_fits
Normal posterior for the overall mean parameter in the fixed effects modelpost_mu_fe
Posterior reference analysis based on a data frame using 2 benchmarkspost_RA
Posterior reference analysis based on a data frame using 3 benchmarkspost_RA_3bm
Posterior reference analysis based on bayesmeta fitspost_RA_fits
Prior reference analysis based on a data frame using 5 benchmarkspri_RA_5bm
Prior reference analysis based on bayesmeta fitspri_RA_fits
Respiratory tract infections datarti
Reference standard deviationsigma_ref