Critical Evidence for Proving Causality to Non-Statisticians in Court
University of Michigan at Ann Arbor - School of Public Health; Employee Motivation and Performance Assessment
Peter D. Jacobson
University of Michigan School of Public Health
Cristina G. Banks
University of California, Berkeley
May 15, 2008
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.
Number of Pages in PDF File: 16working papers series
Date posted: May 15, 2008
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