The attached is a revise and resubmit, and will form part of a Debate in Journal of Epidemiology and Community Health. I have until 25 July to submit. Comments are very welcome. Text is 2100 words. Feel free to comment/track changes in the doc if so inclined.
Have decided that my argument at the end of these slides doesn’t hold up… but there’s something there. I’m now trying to figure out why RR can’t be a constant in an epidemiological law. I’m sure it can’t, but why not?
Here is a link to draft slides for my talk on Friday at the KCL workshop Prediction in Epidemiology and Healthcare, organised by Jonathan Fuller and Luis Flores:
I’m re-working a paper on risk relativism in response to some reviewer comments, and also preparing a talk on the topic for Friday’s meeting at KCL, “Prediction in Epidemiology and Healthcare”. The paper originates in Chapter 8 of my book, where I identify some possible explanations for “risk relativism” and settle on the one I think is best. Briefly, I suggest that there isn’t really a principled way of distinguishing “absolute” and “relative” measures, and instead explain the popularity of relative risk by its superficial similarity to a law of physics, and its apparent independence of any given population. These appearances are misleading, I suggest.
In the paper I am trying to develop the suggestion a bit into an argument. Two remarks by reviewers point me in the direction of further work I need to do. One is the question as to what, exactly, the relation between RR and law of nature is supposed to be. Exactly what character am I supposing that laws have, or that epidemiologists think laws have, such that RR is more similar to a law-like statement than, say, risk difference, or population attributable fraction?
The other is a reference to a literature I don’t know but certainly should, concerning statistical modelling in the social sciences. I am referred to a monograph by Achen in 1982, and a paper by Jan Vandebroucke in 1987, both of which suggest – I gather – a deep scepticism about statistical modelling in the social sciences. Particularly thought-provoking is the idea that all such models are “qualitative descriptions of data”. If there is any truth in that, then it is extremely significant, and deserves unearthing in the age of big data, Google Analytics, Nate Silver, and generally the increasing confidence in the possibility of accurately modelling real world situations, and – crucially – generating predictions out of them.
A third question concerns the relation between these two thoughts: (i) the apparent law-likeness of certain measures contrasted with the apparently population-specific, non-general nature of others; and (ii) the limitations claimed for statistical modelling in some quarters contrasted with confidence in others. I wonder whether degree of confidence has anything to do with perceived law-likeness. One’s initial reaction would be to doubt this: when Nate Silver adjusts his odds on a baseball outcome, he surely does not take himself to be basing his prediction on a law-like generalisation. Yet on reflection, he must be basing it on some generalisation, since the move from observed to unobserved is a kind of generalising. What more, then, is there to the notion of a law, than generalisability on the basis of instances? It is surprising how quickly the waters deepen.
Having neglected this blog for several months I find myself suddenly swamped with things to write about. My book has been translated into Korean by Hyundeuk Cheon, Hwang Seung-sik, and Mr Jeon, and judging by their insightful comments and questions they have done a superb and careful job. Next week there is a workshop on Prediction in Epidemiology and Healthcare at KCL, organised by Jonathan Fuller and Luis Jose Flores, which promises to be exciting. Coming up in August is the World Congress of Epidemiology, where I’m giving two talks, hopefully different ones – one on stability for a session on translation and public engagement, and one on the definition of measures of causal strength as part of a session for the next Dictionary of Epidemiology. And I’m working on a paper on risk relativism which has been accepted by Journal of Epidemiology and Community Health subject to revisions in response to the extremely interesting comments of 5 reviewers – I think this is possibly the most rigorous and most useful review process I have encountered. Thus this is a promissory note, by which I hope to commit my conscience to writing here about risk relativism, stability and measures of causal strength in the coming weeks.
I surely should have posted this earlier, but it’s currently in progress, and very stimulating.
Yesterday I briefed the media on my work and recent book on philosophy of epidemiology, ahead of next week’s launch event at the University of Johannesburg, and today one piece appeared in the Times (here) and two (here and here) in the Star. All the pieces are reasonably fair, and the latter two in particular are more conceptually focused, and thus quite a nice reflection of what I try to do. But it’s interesting for me that what grabbed the most attention were largely empirical claims. A couple of radio stations picked up on the claim that the vitamin supplements industry is a “con”, appearing in the Times piece, and I was interviewed at lunchtime today by Talk 702 and RSG. Both homed in on my claims about vitamins. Talk 702 asked if I expected any defamation actions. I guess this is how the media works – you never quite know which part of what you say is going to be amplified over the rest. That said, I am very grateful to the Times journalist that the context of my “con” claim was included in the piece.
For interest, I thought I would upload the presentation I gave yesterday. Not much about vitamins in there, you will see: 2013-09-10 Media Briefing – Philosophy of Epidemiology