Design-Based Covariate Adjustments in Paired Experiments

Autor/inn/en	Wu, Edward; Gagnon-Bartsch, Johann A.
Titel	Design-Based Covariate Adjustments in Paired Experiments
Quelle	In: Journal of Educational and Behavioral Statistics, 46 (2021) 1, S.109-132 (24 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Wu, Edward)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998620941469
Schlagwörter	Experiments; Groups; Research Design; Statistical Analysis; Randomized Controlled Trials; Intervention; Program Effectiveness; Algebra; Middle Schools; High Schools; Texas + Suchen Sie Ihr Suchwort? Erprobung; Forschungsdesign; Statistische Analyse; Middle school; Mittelschule; Mittelstufenschule; High school; Oberschule
Abstract	In paired experiments, participants are grouped into pairs with similar characteristics, and one observation from each pair is randomly assigned to treatment. The resulting treatment and control groups should be well-balanced; however, there may still be small chance imbalances. Building on work for completely randomized experiments, we propose a design-based method to adjust for covariate imbalances in paired experiments. We leave out each pair and impute its potential outcomes using any prediction algorithm such as lasso or random forests. This method addresses a unique trade-off that exists for paired experiments. By addressing this trade-off, the method has the potential to improve precision over existing methods. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01