Design-Robust Meta-Analysis via Variance-Function Models R package drmeta version 0.1.0 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. Software Depends: R (>= 4.1.0) Imports: grDevices, graphics, stats, utils Suggests: ggplot2 (>= 3.4.0), knitr, metafor (>= 4.0.0), rmarkdown, testthat (>= 3.0.0) Subir Hait <haitsubi@msu.edu> Comprehensive R Archive Network (CRAN) Subir Hait [aut, cre] (ORCID: <https://orcid.org/0009-0004-9871-9677>) MIT + file LICENSE (https://CRAN.R-project.org/package=drmeta/LICENSE) 2026-04-08 application/tgz https://CRAN.R-project.org/package=drmeta doi:10.32614/CRAN.package.drmeta