README.md
In drmeta: Design-Indexed Location-Scale Meta-Analysis

drmeta

Design-Indexed Location-Scale Meta-Analysis

drmeta fits meta-analytic location-scale models in which residual between-study heterogeneity is an exponential function of a prespecified design-robustness index:

y_i ~ N( x_i'beta ,  v_i + tau0^2 * exp(-gamma * DR_i) )

The constrained form imposes gamma >= 0, encoding the directional hypothesis that unexplained heterogeneity does not increase as design robustness improves. Setting gamma = 0 recovers the conventional random-effects model exactly.

A scale model changes how precision is allocated across studies. It does not identify or remove a systematic design-linked shift in the conditional mean. If the mean varies with design robustness, the scale-only pooled estimate is a model-dependent weighted average, not the effect of a hypothetical perfectly designed study. Supply location moderators via mods when design-linked mean differences are plausible, and do not describe scale reweighting as confounding adjustment.

# install.packages("remotes")
remotes::install_github("causalfragility-lab/drmeta")

library(drmeta)

bcg <- utils::read.csv(
  system.file("extdata", "bcg_design_robustness.csv", package = "drmeta")
)

# Constrained fit
fit <- drmeta(yi = bcg[["yi"]], vi = bcg[["vi"]], dr = bcg[["dr"]])
summary(fit)

# Minimum comparison set
re  <- drmeta(bcg[["yi"]], bcg[["vi"]], bcg[["dr"]], gamma_fixed = 0)  # random effects
ls  <- drmeta(bcg[["yi"]], bcg[["vi"]], bcg[["dr"]], constrained = FALSE)
jls <- drmeta(bcg[["yi"]], bcg[["vi"]], bcg[["dr"]], mods = 1 - bcg[["dr"]])

# Interpretation over observed support, not extrapolated to [0,1]
dr_scale_attenuation(fit)
dr_plot_vfun(fit)

# Boundary-aware inference and influence
drmeta_bootstrap_gamma(fit, B = 999, seed = 1)
dr_loo(fit)

Report gamma together with the observed range of the design index, the convergence and boundary status, and the fitted variance ratio or attenuation over a prespecified contrast within observed support. The magnitude of gamma alone depends on the scaling of the index and is not an invariant measure of design sensitivity.

For a primary analysis, construct the design index without using the realized effect estimate, its standard error, its p-value, its confidence interval, or any outcome-dependent diagnostic. Scores that use such information define an exploratory analysis.

Current version 0.2.2. NEWS.md documents the breaking changes from 0.1.0, including the functions removed and the withdrawal of the design-explained variance decomposition, and the 0.2.1 change to drmeta_bootstrap_gamma(), which now short-circuits when the constrained scale gradient is estimated at the boundary.

MIT