GATE: Estimation of the Grouped Average Treatment Effects (GATEs)...

In evalITR: Evaluating Individualized Treatment Rules

Estimation of the Grouped Average Treatment Effects (GATEs) in Randomized Experiments

Description

Estimates grouped average treatment effects from a continuous score.

Usage

GATE(T, tau, Y, ngates = 5, centered = FALSE)

Arguments

T	Binary treatment indicator (0 or 1).
tau	Continuous score vector.
Y	Outcome vector.
ngates	Number of groups (at least 2).
centered	Whether to center outcomes before estimation.

Details

Standard errors account for estimated group cutoffs and assume continuous treatment effects at the boundaries. Ties are broken randomly; use set.seed() for reproducibility. Both arms need at least two observations. Empty group arms return NA standard errors.

Value

A list with group estimates gate and standard errors sd, ordered by increasing score.

Author(s)

Michael Lingzhi Li, Technology and Operations Management, Harvard Business School [e-mail], https://www.michaellz.com/;

References

Imai and Li (2022). “Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments”,

Examples

T = c(1,0,1,0,1,0,1,0)
tau = c(0,0.1,0.2,0.3,0.4,0.5,0.6,0.7)
Y = c(4,5,0,2,4,1,-4,3)
gatelist <- GATE(T,tau,Y,ngates=2)
gatelist$gate
gatelist$sd

evalITR documentation built on Sept. 7, 2026, 9:06 a.m.