# Designing Transportable Experiments

arXiv: https://arxiv.org/abs/2009.03860 · HTML: https://mlsanity.com/paper/2009.03860/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Sep 2020.

## Built on by (most cited first, 1 of 1)

- [Target-Weighted Neyman Allocation: Experimental Design for Heterogeneous Treatment Effects under Population Shift](https://mlsanity.com/paper/2608.06512/) (2026)

## Abstract (arXiv)

We consider the problem of designing a randomized experiment on a source population to estimate the Average Treatment Effect (ATE) on a target population. We propose a novel approach which explicitly considers the target when designing the experiment on the source. Under the covariate shift assumption, we design an unbiased importance-weighted estimator for the target population's ATE. To reduce the variance of our estimator, we design a covariate balance condition (Target Balance) between the treatment and control groups based on the target population. We show that Target Balance achieves a higher variance reduction asymptotically than methods that do not consider the target population during the design phase. Our experiments illustrate that Target Balance reduces the variance even for small sample sizes.