Pre-order Regression Discontinuity Design

The Regression Discontinuity Design (RDD) is a powerful method to uncover causal effects in settings where traditional randomization isn’t feasible. It leverages a clear threshold or cutoff point to assign treatments, allowing you to estimate the impact of an intervention with precision. By comparing outcomes just above and below this threshold, RDD identifies the direct influence of the treatment, making it ideal for settings where policy changes, educational interventions, or social programs are at play.

RDD is especially valuable because it closely mimics the rigor of experimental design in real-world situations. Whether in education, healthcare, or policy analysis, RDD allows you to make causal inferences by focusing on participants near the cutoff, who are similar in all aspects except their treatment status. This method delivers highly credible results by isolating the treatment effect in a controlled, localized way. Embrace RDD for accurate, impactful results in your analysis—without the need for full randomization.