Causality and Association: The Statistical and Legal Approaches
K. Mengersen, S. A. Moynihan, R. L. Tweedie

TL;DR
This paper explores the intersection of statistical and legal methods for establishing causation, proposing a systematic framework for evaluating causality in observational studies and legal cases involving epidemiological data.
Contribution
It introduces a variation of the Bradford Hill approach for causality testing and clarifies the distinction between scientific and legal concepts of causation.
Findings
Proposes a systematic series of tests for causality in observational data
Links scientific causality testing with legal probabilistic standards
Clarifies terminology differences between legal and scientific causation
Abstract
This paper discusses different needs and approaches to establishing ``causation'' that are relevant in legal cases involving statistical input based on epidemiological (or more generally observational or population-based) information. We distinguish between three versions of ``cause'': the first involves negligence in providing or allowing exposure, the second involves ``cause'' as it is shown through a scientifically proved increased risk of an outcome from the exposure in a population, and the third considers ``cause'' as it might apply to an individual plaintiff based on the first two. The population-oriented ``cause'' is that commonly addressed by statisticians, and we propose a variation on the Bradford Hill approach to testing such causality in an observational framework, and discuss how such a systematic series of tests might be considered in a legal context. We review some…
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