*! ml_sens.sthlp — metaLong for Stata 14.1

ml_sens — Time-Varying Sensitivity Analysis via Longitudinal ITCV

Syntax

ml_sens yi vi [if] [in] ,
study(varname)
time(varname)
metafile(filename)
[alpha() delta() saving() replace]

Description

ml_sens computes the Impact Threshold for a Confounding Variable (ITCV) at
each follow-up time point. Two versions: raw ITCV (to nullify the estimate) and
significance-adjusted ITCV_adj (to render the estimate non-significant). A time
point is "fragile" if ITCV_adj < delta.

Required options

study(varname), time(varname) — As in ml_meta.

metafile() — Path to dataset saved by ml_meta.

Options

alpha() — Significance level. Default 0.05.

delta() — Fragility threshold. Time points with
ITCV_adj < delta are flagged as fragile. Default 0.15.

saving() / replace — Save results.

Returned values

r(sens) — Matrix: time theta se df sy r_effect itcv itcv_alpha fragile.

r(itcv_min), r(itcv_mean), r(frag_prop).

Formulas

sy2 = sum(wi*(yi - theta)^2) / sum(wi) [weighted variance of effects]

r = theta / sqrt(theta^2 + sy2) [correlation-scale effect]

ITCV = sqrt(|r|)

theta* = |theta| - crit*se; if theta* > 0: ITCV_adj = sqrt(|r*|), else 0.

Reference

Frank, K.A. (2000). Sociological Methods & Research, 29(2), 147-194.