The Rules of Inference
Lee Epstein, Gary King. 2002.
"The Rules of Inference".
University of Chicago Law Review, 69, Pp. 1–209.

Abstract
Although the term “empirical research” has become commonplace in legal scholarship over the past two decades, law professors have, in fact, been conducting research that is empirical – that is, learning about the world using quantitative data or qualitative information – for almost as long as they have been conducting research. For just as long, however, they have been proceeding with little awareness of, much less compliance with, the rules of inference, and without paying heed to the key lessons of the revolution in empirical analysis that has been taking place over the last century in other disciplines. The tradition of including some articles devoted to exclusively to the methododology of empirical analysis – so well represented in journals in traditional academic fields – is virtually nonexistent in the nation’s law reviews. As a result, readers learn considerably less accurate information about the empirical world than the studies’ stridently stated, but overconfident, conclusions suggest. To remedy this situation both for the producers and consumers of empirical work, this Article adapts the rules of inference used in the natural and social sciences to the special needs, theories, and data in legal scholarship, and explicate them with extensive illustrations from existing research. The Article also offers suggestions for how the infrastructure of teaching and research at law schools might be reorganized so that it can better support the creation of first-rate empirical research without compromising other important objectives.
See Also
- [Paper] Building An Infrastructure for Empirical Research in the Law (2003)
- [Paper] Finding New Information for Ecological Inference Models: A Comment on Jon Wakefield, 'Ecological Inference in 2X2 Tables' (2004)
- [Paper] Bayesian and Frequentist Inference for Ecological Inference: The RxC Case (2001)
- [Presentation] Matching Methods for Observational and Experimental Causal Inference (Facultad Latinoamericana de Ciencias Sociales) (2023)
- [Paper] The Essential Role of Statistical Inference in Evaluating Electoral Systems: A Response to DeFord et Al. (2023)
- [Presentation] Simplifying Matching Methods for Causal Inference (University of Wisconsin at Madison) (2022)
- [Paper] A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results (2021)
- [Book] Designing Social Inquiry: Scientific Inference in Qualitative Research, New Edition (2021)