evalITR (version 1.1.0)

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

Value

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

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.

Author

Michael Lingzhi Li, Technology and Operations Management, Harvard Business School , https://www.michaellz.com/;

Details

See GATE for inference details.

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