evalITR (version 1.1.0)

GATE: 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)

Value

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

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

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.

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