sensitivity_meditcv: Mediation ITCV (medITCV) for pathway-specific robustness

In RobustMediate: Causal Mediation Analysis with Diagnostics and Sensitivity Analysis

Mediation ITCV (medITCV) for pathway-specific robustness

Description

Computes a mediation-specific extension of Kenneth Frank's (2000) Impact Threshold for a Confounding Variable (ITCV) for both pathways of a mediation model:

• a-path: treatment -> mediator

• b-path: mediator -> outcome (controlling for treatment)

The mediation ITCV (medITCV) quantifies how strong an unmeasured confounder would need to be, in terms of the product r_{XC} \cdot r_{YC}, to invalidate inference for each pathway.

Usage

sensitivity_meditcv(x, alpha = 0.05)

Arguments

x	A robmedfit object returned by robustmediate().
alpha	Significance level. Default is 0.05.

Value

An object of class "meditcv": a named list with elements a_path, b_path, indirect, and alpha. Each pathway element contains the observed partial correlation, critical partial correlation, medITCV value, and benchmark confounder impacts.

References

Frank, K. A. (2000). Impact of a confounding variable on a regression coefficient. Sociological Methods & Research, 29(2), 147–194.

See Also

plot_meditcv(), print.meditcv()

Examples

data(sim_mediation)
  fit <- robustmediate(
    X ~ Z1 + Z2, M ~ X + Z1 + Z2, Y ~ X + M + Z1 + Z2,
    data = sim_mediation, R = 20, verbose = FALSE
  )
med <- sensitivity_meditcv(fit)
print(med)
plot_meditcv(med)

RobustMediate documentation built on April 16, 2026, 5:08 p.m.