Use design-based methods for causal inference in randomized studies of individuals or groups¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The brief recommends broadening knowledge of design-based methods by describing "their key concepts and how they compare to model-based methods," presenting the approach's rudiments "using simple mathematical notation" and discussing the underlying intuition "for designs where individuals or groups are randomized." Researchers conducting randomized evaluations can use this brief to understand and apply design-based causal inference.

Design Implications¶

Context¶

Requirements¶

• A design in which individuals or groups are randomized, since the intuition underlying the theory is discussed for such designs

Constraints¶

Target Learners¶

• Education researchers and evaluation analysts

Target Learning Goals¶

• Applying design-based methods to estimate causal effects in randomized studies

Affordances¶

• Design Based Causal Inference Approach

Related Strategies¶

Examples¶

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Key Sources¶

• Peter Z. Schochet. (2017). What is Design-Based Causal Inference and Why Should I Use It?. Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance. https://ies.ed.gov/ncee