Accounting for Student Disadvantage in Value-Added Models

Autor/inn/en	Parsons, Eric; Koedel, Cory; Tan, Li
Titel	Accounting for Student Disadvantage in Value-Added Models
Quelle	In: Journal of Educational and Behavioral Statistics, 44 (2019) 2, S.144-179 (36 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998618803889
Schlagwörter	Value Added Models; Economically Disadvantaged; Academic Achievement; Low Income Students; Disadvantaged Youth; Student Characteristics; Simulation; Family Income; Error of Measurement; Teacher Competencies + Suchen Sie Ihr Suchwort? Schulleistung; Benachteiligter Jugendlicher; Simulation program; Simulationsprogramm; Familieneinkommen; Messfehler; Lehrkunst
Abstract	We study the relative performance of two policy-relevant value-added models--a one-step fixed effect model and a two-step aggregated residuals model--using a simulated data set well grounded in the value-added literature. A key feature of our data generating process is that student achievement depends on a continuous measure of economic disadvantage. This is a realistic condition that has implications for model performance because researchers typically have access to only a noisy, binary measure of disadvantage. We find that one- and two-step value-added models perform similarly across a wide range of student and teacher sorting conditions, with the two-step model modestly outperforming the one-step model in conditions that best match observed sorting in real data. A reason for the generally superior performance of the two-step model is that it better handles the use of an error-prone, dichotomous proxy for student disadvantage. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01