ml_benchmark — Benchmark Calibration of ITCV Against Observed Covariates

Syntax

ml_benchmark yi vi [if] [in] ,
study(varname)
time(varname)
metafile(filename)
sensfile(filename)
covariates(varlist)
[options]

Description

For each covariate Z and time t: centres Z, fits weighted meta-regression
yi ~ 1 + Z_centred with cluster-robust SE, extracts partial correlation
r_partial = t / sqrt(t^2 + df), and compares to the ITCV_adj(t) threshold.
If |r_partial| >= ITCV_adj(t), an unobserved confounder of that strength
would suffice to nullify the effect — calibrating the fragility threshold.

Options

covariates(varlist) — One or more numeric study-level moderators.

mink() — Minimum studies per time point. Default 3 (one more
than ml_meta, since regression needs additional degrees of freedom).

nosmallsample — Z-based inference instead of t(k-2).

saving() / replace — Save results dataset.

Saved dataset variables

time, covariate, k, r_partial, t_stat, df, p_val, itcv_alpha, beats