Critical Evidence for Proving Causality (i.e., Causation) to Non-Statisticians in Court

Abstract

No contemporary guide exists for using statistics to prove causality in court. We outline a new theory explaining comprehension of causal graphs, and claim four hallmarks of causality are critical: Association, Prediction, Exclusion of Alternative Explanations, and Dose Dependence. We test our theory in 63 smoking lawsuits, finding that movants who use all four hallmarks are significantly more likely to prevail (p <.05); moreover, number of hallmarks predicts likelihood of prevailing. Results also suggest courts are especially swayed by evidence excluding alternative explanations and/or demonstrating dose dependence (p < .00001). We close with guidelines for using causal graphs in court.