dot-predict_effects: Predict mean potential outcome under a dose pair (x, x_ref)

In RobustMediate: Causal Mediation Analysis with Diagnostics and Sensitivity Analysis

Predict mean potential outcome under a dose pair (x, x_ref)

Description

Implements the g-computation identification formula for the NDE and NIE:

NDE(x, x^*) = E[Y(x, M(x^*))] - E[Y(x^*, M(x^*))]

NIE(x, x^*) = E[Y(x, M(x))] - E[Y(x, M(x^*))]

The mediator is predicted at the individual level (not as a scalar mean), correctly marginalising over each person's covariate values.

Usage

.predict_effects(models, data, x, x_ref, treat_var, med_var, out_var)

Arguments

models	List with elements treatment, mediator, outcome.
data	Original data frame.
x	Dose value (the "treated" level).
x_ref	Reference dose (counterfactual baseline).
treat_var	Character. Name of treatment variable.
med_var	Character. Name of mediator variable.
out_var	Character. Name of outcome variable.

Value

Named numeric vector: NDE, NIE, TE.

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