A regression discontinuity design compares units immediately on either side of a treatment-assignment cutoff. Its causal interpretation requires potential outcomes to vary continuously through that cutoff in the absence of treatment.
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Regression Discontinuity Design (RDD) is a quasi-experimental research design used to identify causal effects of interventions by assigning a cutoff or threshold score on a continuous assignment variable. When an intervention is implemented based on a specific criterion, RDD can help estimate the treatment effect by comparing observations just above and below this cutoff. This method is particularly useful when random assignment is not feasible, allowing researchers to draw causal inferences from observational data. ### Key Components of RDD 1.