Policy Research and Stats

In the past I bashed on Andrew Exum for being too dismissive of stats work in IR, so it's only fair that I praise him for running this guest-post on his to do policy-relevant conflict stats analysis. I haven't read the paper Charlie Simpson is criticizing, but as a general lesson the post is good. Some of them may be less relevant for academics than policy folks -- "Moneyball that shit and find the COIN version of on-base percentage or WHIP" is about exploiting arbitrage opportunities and snapping up under-valued assets at basement prices... not really what academic work is about -- but that's a good lesson too. Methodological approaches that are valid in some contexts are not appropriate in all contexts. Knowing the difference is half the battle. Maybe the most important half.

A few caveats to Simpson's post:

- #3 applies to regression as much as cross-tabs or whatever. I think her point is that multivariate analysis is what is needed, but that's not what she actually says so I can't be too sure.

- #4 is a very good point. Which is why...

- ...It sucks that #5 is wrong. Well, wrong at the end. Not all variables need to be measured at the same level of analysis. That's what HLMs are for. I'm becoming an HLM advocate more and more all the time, so I'd like to see this get out there more.