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drmeta  

Design-Robust Meta-Analysis via Variance-Function Models
View on CRAN: Click here


Download and install drmeta package within the R console
Install from CRAN:
install.packages("drmeta")

Install from Github:
library("remotes")
install_github("cran/drmeta")

Install by package version:
library("remotes")
install_version("drmeta", "0.1.0")



Attach the package and use:
library("drmeta")
Maintained by
Subir Hait
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-08
Latest Update: 2026-04-08
Description:
Implements Design-Robust Meta-Analysis (DR-Meta), a variance-function random-effects framework in which between-study heterogeneity is modelled as a function of a study-level design robustness index, allowing heterogeneity to depend systematically on study quality or design strength rather than being treated as a single nuisance parameter. The package provides profiled restricted maximum likelihood (REML) estimation of the overall effect and variance-function parameters, study-specific weights, heterogeneity diagnostics (tau-squared, I-squared), influence and leave-one-out analysis, and graphical tools including forest plots and influence plots. The DR-Meta framework nests classical fixed-effects and standard random-effects meta-analysis as special cases, making it a strict generalisation of existing approaches.
How to cite:
Subir Hait (2026). drmeta: Design-Robust Meta-Analysis via Variance-Function Models. R package version 0.1.0, https://cran.r-project.org/web/packages/drmeta. Accessed 12 Sep. 2026.
Previous versions and publish date:
(2026-08-24 21:10), 0.1.0 (2026-04-08 20:40)
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Functions, R codes and Examples using the drmeta R package
Full drmeta package functions and examples
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