Tomorrow I’ll be giving a seminar in our faculty on inference in complex systems (like the health service, or social services, or local government, or society more generally). It’s the latest talk on this subject that is really gelling now into something of a manifesto. Rick Hood and I intend to send off the paper version before Xmas, so I won’t say more about the substance of it here (and the slides are just a bunch of aide-memoire images), other than to list the references, which contains some of my favourite sources on data+science:
- Regina Nuzzo, “Fooling Ourselves“, Nature, 8 Oct 2015.
- Various artists, “Veto on the use of null hypothesis testing and p intervals: right or wrong?“, Taylor & Francis editor resources online, 16 November 2015.
- Andrew Gelman & Eric Loken, “The garden of forking paths: Why multiple comparisons can be a problem, even when there is no ‘fishing expedition’ or ‘p-hacking’ and the research hypothesis was posited ahead of time“, 14 Nov 2013.
- Stephen Ziliak & Deirdre McCloskey, “The Cult of Statistical Significance: how the standard error costs us jobs, justice and lives”, University of Michigan Press, 2008.
- Gerd Gigerenzer, “Adaptive Thinking: rationality in the real world”, Oxford University Press, 2000.
- Peter Lipton, “Inference to the Best Explanation” (2nd ed.), Routledge, 2004.
- Charles Manski, “Identification Problems in the Social Sciences”, Harvard University Press, 1992.
- Edward Leamer, “Let’s take the con out of econometrics“, The American Economic Review (1983); 73(1): 31-43.
- Ray Pawson & Nicholas Tilley, “Realistic Evaluation”, Sage, 1997.
- Paul Cilliers, “Complexity, Deconstruction and Relativism“, Theory Culture and Society (2005); 22: 255.
- Rick Hood. “Complexity and Integrated Working in Children’s Services“, British Journal of Social Work (2012): 1–17.
I deliberately omit the methodologically detailed papers from this list, but in the main you should look into Bayesian modelling, generalised coarsening, generalised instrumental variable models, structural equation models, and their various intersections.