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ra4bayesmeta (version 1.0-8)

Reference Analysis for Bayesian Meta-Analysis

Description

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) . 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.

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Version

Install

install.packages('ra4bayesmeta')

Monthly Downloads

163

Version

1.0-8

License

GPL (>= 2)

Maintainer

Manuela Ott

Last Published

October 6th, 2023

Functions in ra4bayesmeta (1.0-8)

Posterior reference analysis based on bayesmeta fits

Reference analysis plot based on bayesmeta fits: Plot heterogeneity benchmark priors and the corresponding marginal posteriors

Model fitting for reference analysis using 2 benchmarks: Posterior inference for benchmark and actual heterogeneity priors

Reference analysis plot based on a data frame using 2 benchmarks: Plot heterogeneity benchmark priors and the corresponding marginal posteriors

Optimization function for the SGC(m) prior: Approximate Jeffreys reference posterior

Optimization function for the SGC(m) prior: Adjust the prior to a target relative latent model complexity (RLMC)

Posterior reference analysis based on a data frame using 3 benchmarks

Posterior reference analysis based on a data frame using 2 benchmarks

Reference analysis plot based on a data frame using 5 benchmarks: Plot heterogeneity benchmark priors and the corresponding marginal posteriors

Normal posterior for the overall mean parameter in the fixed effects model

Prior reference analysis based on a data frame using 5 benchmarks

Reference standard deviation

Prior reference analysis based on bayesmeta fits

Respiratory tract infections data

fit_models_RA_5bm

Model fitting for reference analysis using 5 benchmarks: Posterior inference for benchmark and actual heterogeneity priors

ra4bayesmeta-package

tools:::Rd_package_title("ra4bayesmeta")

Auricular acupuncture data

Optimization function for the SIGC(M) prior: Adjust the prior to a target relative latent model complexity (RLMC)

Optimization function for the SIGC(m) prior: Approximate Jeffreys reference posterior

Approximate moment-based Hellinger distance computation between two probability densities

Hellinger distance between two probability densities

Calibration of the Hellinger distance

Hellinger distance between marignal posterior densities of two bayesmeta fits

Density function of the square-root generalized conventional (SGC) benchmark prior

Acute otitis media data

Density function of the square-root inverse generalized conventional (SIGC) benchmark prior