When ANOVA gets it wrong: A re-introduction to the Regression Discontinuity design

When observations are not randomly assigned to conditions, assumptions of traditional estimation methods such as ANOVA or linear regression will be violated and can lead to biased and inconsistent estimators. However, there exist quasi-experimental designs that can be used to infer causality. One of these designs, the Regression Discontinuity (RD) design, allows for the drawing of proper causal conclusions when observations are not randomized to...