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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
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.