het.test: The Heterogeneity Test for Grouped Average Treatment Effects...

In evalHTE: Evaluating Heterogeneous Treatment Effects

The Heterogeneity Test for Grouped Average Treatment Effects (GATEs) in Randomized Experiments

Description

Tests whether treatment effects are equal across score groups.

Usage

het.test(D, tau, Y, ngates = 5, centered = TRUE)

Arguments

D	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

Uses het.test for inference.

Value

A list with test statistic stat and p-value pval.

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

D = 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)
hettestlist <- het.test(D,tau,Y,ngates=2)
hettestlist$stat
hettestlist$pval

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