Revisiting Randomization with the Cube Method

Fuente: arXiv
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Hauptverfasser: Davezies, Laurent, Hollard, Guillaume, Merino, Pedro Vergara
Format: Preprint
Veröffentlicht: 2024
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author Davezies, Laurent
Hollard, Guillaume
Merino, Pedro Vergara
author_facet Davezies, Laurent
Hollard, Guillaume
Merino, Pedro Vergara
contents We introduce a new randomization procedure for experiments based on the cube method, which achieves near-exact covariate balance. This ensures compliance with standard balance tests and allows for balancing on many covariates, enabling more precise estimation of treatment effects using pre-experimental information. We derive theoretical bounds on imbalance as functions of sample size and covariate dimension, and establish consistency and asymptotic normality of the resulting estimators. Simulations show substantial improvements in precision and covariate balance over existing methods, particularly when the number of covariates is large.
format Preprint
id arxiv_https___arxiv_org_abs_2407_13613
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Revisiting Randomization with the Cube Method
Davezies, Laurent
Hollard, Guillaume
Merino, Pedro Vergara
Econometrics
We introduce a new randomization procedure for experiments based on the cube method, which achieves near-exact covariate balance. This ensures compliance with standard balance tests and allows for balancing on many covariates, enabling more precise estimation of treatment effects using pre-experimental information. We derive theoretical bounds on imbalance as functions of sample size and covariate dimension, and establish consistency and asymptotic normality of the resulting estimators. Simulations show substantial improvements in precision and covariate balance over existing methods, particularly when the number of covariates is large.
title Revisiting Randomization with the Cube Method
topic Econometrics
url https://arxiv.org/abs/2407.13613