drmeta: Design-Robust Meta-Analysis via Variance-Function Models
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.
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