Estimators for Clustered Education RCTs Using the Neyman Model for Causal Inference

Autor/in	Schochet, Peter Z.
Titel	Estimators for Clustered Education RCTs Using the Neyman Model for Causal Inference
Quelle	In: Journal of Educational and Behavioral Statistics, 38 (2013) 3, S.219-238 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998611432176
Schlagwörter	Computation; Causal Models; Statistical Inference; Nonparametric Statistics; Educational Experiments; Experimental Groups; Control Groups; Elementary School Mathematics; Mathematics Achievement; Grade 1; Elementary School Students; Instructional Effectiveness; Mathematics Instruction + Suchen Sie Ihr Suchwort? Kausalanalyse; Inferential statistics; Schließende Statistik; Schulversuch; Elementare Mathematik; Schulmathematik; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; School year 01; 1. Schuljahr; Schuljahr 01; Unterrichtserfolg; Mathematics lessons; Mathematikunterricht
Abstract	This article examines the estimation of two-stage clustered designs for education randomized control trials (RCTs) using the nonparametric Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for the study population (the finite-population model) or randomly selected from a vaguely defined universe (the super-population model). Both approaches allow for heterogeneity of treatment effects. Appropriate estimation methods and asymptotic moments are discussed for each model using simple differences-in-means estimators and those that include baseline covariates. An empirical application using a large-scale education RCT shows that the choice of the finite- or super-population approach can matter. Thus, the choice of framework and sensitivity analyses should be specified and justified in the analysis protocols. (Contains 2 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10