Some theoretical foundations for the design and analysis of randomized experiments

Fuente: arXiv
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Main Authors: Shi, Lei, Li, Xinran
Format: Preprint
Published: 2024
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author Shi, Lei
Li, Xinran
author_facet Shi, Lei
Li, Xinran
contents Neyman[106]'s seminal work in 1923 has been a milestone in statistics over the century, which has motivated many fundamental statistical concepts and methodology. In this review, we delve into Neyman[106]'s groundbreaking contribution and offer technical insights into the design and analysis of randomized experiments. We shall review the basic setup of completely randomized experiments and the classical approaches for inferring the average treatment effects. We shall in particular review more efficient design and analysis of randomized experiments by utilizing pretreatment covariates, which move beyond Neyman's original work without involving any covariate. We then summarize several technical ingredients regarding randomizations and permutations that have been developed over the century, such as permutational central limit theorems and Berry-Esseen bounds, and elaborate on how these technical results facilitate the understanding of randomized experiments. The discussion is also extended to other randomized experiments including rerandomization, stratified randomized experiments, matched pair experiments, cluster randomized experiments, etc.
format Preprint
id arxiv_https___arxiv_org_abs_2406_10444
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Some theoretical foundations for the design and analysis of randomized experiments
Shi, Lei
Li, Xinran
Statistics Theory
62K15, 62J05, 62G05
Neyman[106]'s seminal work in 1923 has been a milestone in statistics over the century, which has motivated many fundamental statistical concepts and methodology. In this review, we delve into Neyman[106]'s groundbreaking contribution and offer technical insights into the design and analysis of randomized experiments. We shall review the basic setup of completely randomized experiments and the classical approaches for inferring the average treatment effects. We shall in particular review more efficient design and analysis of randomized experiments by utilizing pretreatment covariates, which move beyond Neyman's original work without involving any covariate. We then summarize several technical ingredients regarding randomizations and permutations that have been developed over the century, such as permutational central limit theorems and Berry-Esseen bounds, and elaborate on how these technical results facilitate the understanding of randomized experiments. The discussion is also extended to other randomized experiments including rerandomization, stratified randomized experiments, matched pair experiments, cluster randomized experiments, etc.
title Some theoretical foundations for the design and analysis of randomized experiments
topic Statistics Theory
62K15, 62J05, 62G05
url https://arxiv.org/abs/2406.10444