Regression Discontinuity Designs with an Ordinal Running Variable: Evaluating the Effects of Extended Time Accommodations for English-Language Learners

Autor/inn/en	Suk, Youmi; Steiner, Peter M.; Kim, Jee-Seon; Kang, Hyunseung
Titel	Regression Discontinuity Designs with an Ordinal Running Variable: Evaluating the Effects of Extended Time Accommodations for English-Language Learners
Quelle	In: Journal of Educational and Behavioral Statistics, 47 (2022) 4, S.459-484 (26 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/10769986221090275
Schlagwörter	Regression (Statistics); Program Evaluation; Research Design; English Language Learners; Language Proficiency; National Competency Tests; Testing Accommodations; Robustness (Statistics); Scaling; Cutting Scores; National Assessment of Educational Progress + Suchen Sie Ihr Suchwort? Regression; Regressionsanalyse; Programme evaluation; Programmevaluation; Forschungsdesign; Language skill; Language skills; Sprachkompetenz; Testing process; Accessibility (for disabled); Accessibility; Disabled person; Testdurchführung; Testen; Barrierefreiheit; Zugänglichkeit; Behinderter; Widerstandsfähigkeit; Scale construction; Skalenkonstruktion
Abstract	Regression discontinuity (RD) designs are commonly used for program evaluation with continuous treatment assignment variables. But in practice, treatment assignment is frequently based on ordinal variables. In this study, we propose an RD design with an ordinal running variable to assess the effects of extended time accommodations (ETA) for English-language learners (ELLs). ETA eligibility is determined by ordinal ELL English-proficiency categories of National Assessment of Educational Progress data. We discuss the identification and estimation of the average treatment effect (ATE), intent-to-treat effect, and the local ATE at the cutoff. We also propose a series of sensitivity analyses to probe the effect estimates' robustness to the choices of scaling functions and cutoff scores and remaining confounding. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01