In my last post I opinionated about how it's near impossible, in social science research (or media effects, in this case), to account for every possible confounding variable. Now Kevin Drum reviews a new book by Jim Manzi, Uncontrolled, about the same problem, and names it: Causal density. Drum:
If you're studying the orbit of a planet, you can pretty much assume there's only one important cause of the planet's movement: gravity. Causal density is low. In medicine, there are more things to worry about, but a lot of problems are still tractable. Causal density is moderate. But in human affairs, there are lots of causes of everything, there are causes of the causes, and the causes often interact in complex ways. Causal density is very high, which means it's very hard to make sure you've accounted for everything. No matter how sophisticated your statistical tools are, it's always possible that something you haven't thought of is lurking in the background and throwing off your results.
The book is apparently mostly about business and policy, but it looks highly relevant for for social scientists as well. I'm adding it to my stack of books I hope to read sometime soon.
This post has not been revised since publication.