What Is Design-Based Causal Inference for RCTs and Why Should I Use It? NCEE 2017-4025

Autor/in	Schochet, Peter Z.
Institution	Decision Information Resources, Inc.; National Center for Education Evaluation and Regional Assistance (ED)
Titel	What Is Design-Based Causal Inference for RCTs and Why Should I Use It? NCEE 2017-4025
Quelle	(2017), (16 Seiten) PDF als Volltext (1); PDF als Volltext kostenfreie Datei (2) Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Design; Randomized Controlled Trials; Quasiexperimental Design; Research Methodology; Educational Research; Intervention; Measures (Individuals); Equations (Mathematics); Computation; Program Evaluation; Program Effectiveness; Evaluation Methods; Experiments; Models; Regression (Statistics); Hierarchical Linear Modeling; Least Squares Statistics + Suchen Sie Ihr Suchwort? Research method; Forschungsmethode; Bildungsforschung; Pädagogische Forschung; Messdaten; Equations; Mathematics; Gleichungslehre; Programme evaluation; Programmevaluation; Erprobung; Analogiemodell; Regression; Regressionsanalyse
Abstract	Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies. The impact estimators are derived using the building blocks of experimental designs with minimal assumptions, and have good statistical properties. The methods apply to randomized controlled trials (RCTs) and quasi-experimental designs (QEDs) with treatment and control (comparison) groups. Importantly, design-based estimators are acceptable for What Works Clearinghouse (WWC) evidence reviews (Scher and Cole, 2017). Although the fundamental concepts that underlie design-based methods are straightforward, the literature on these methods is technical, with detailed mathematical proofs required to formalize the theory. Thus, the daunting task of wading through this literature might discourage some education researchers from using design-based methods in favor of more traditional "model-based" methods, such as hierarchical linear modeling (HLM) (Raudenbush and Bryk, 2002). This brief aims to broaden knowledge of design-based methods by providing intuition on their key concepts and how they compare to model-based methods as typically implemented. Using simple mathematical notation, the brief is geared toward education researchers with a good knowledge of evaluation designs and HLM. The discussion synthesizes Schochet (2016), omitting details for brevity and accessibility. The focus is on RCTs, although key concepts apply also to QEDs. [For related reports see: "Comparing Impact Findings from Design-Based and Model-Based Methods: An Empirical Investigation. NCEE 2017-4026" (ED575021) and "Multi-Armed RCTs: A Design-Based Framework. NCEE 2017-4027" (ED575022).] (ERIC).
Anmerkungen	National Center for Education Evaluation and Regional Assistance. Available from: ED Pubs. P.O. Box 1398, Jessup, MD 20794-1398. Tel: 877-433-7827; Web site: http://ies.ed.gov/ncee/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01