Must-read: Andrew Gelman and Cosma Rohilla Shalizi: “Philosophy and the practice of Bayesian statistics”

Andrew Gelman and Cosma Rohilla Shalizi (2011): Philosophy and the Practice of Bayesian Statistics: “A substantial school in the philosophy of science…

…identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science.

Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework.

Must-Read: Andrew Gelman: Asking the Question Is the Most Important Step

Must-Read: Something very, very peculiar is going on with middle-aged American whites in the Bush 43 and Obama years–much more so for women–and it is distinctly odd:

Andrew Gelman: Andrew Gelman: Asking the Question Is the Most Important Step: “I worked super-hard to make the graph… that helped me understand what was going on…

Asking the question is the most important step Statistical Modeling Causal Inference and Social Science

…But, from the social science perspective, what’s far more important is asking the question in the first place, which is what Case and Deaton…. That’s what got the ball rolling. (And, to be fair, they also rolled the ball most of the way.) I’m happy to have refined their analyses and, as noted yesterday, I wasn’t so thrilled by one of Case’s offhand remarks, but let me emphasize that all this discussion is predicated on their effort, on their knowing what to look at, which in turn derives from their justly well-respected research on public health and economic development. That’s the big picture….

Statisticians such as myself have our place in the research ecosystem, but all the bias correction and modeling and clever graphics in the world won’t help you if you don’t know what to look at. And in this particular example, I had no idea of looking at any of this until I was pointed to Case and Deaton’s work…. None of our contributions could’ve happened without the work by the original authors. It’s not Us vs. Them. It’s never Us vs. Them. It’s Us and Them. Or, perhaps more accurately, THEM followed by a little bit of us. And that’s one reason I want them to respect and understand us, not to fear us and be defensive”