An Integrative Metaregression Framework for Descriptive Epidemiology – http://www.amazon.com/Integrative-Metaregression-Descriptive-Epidemiology-Publications/dp/0295991844
Tag Archives: dismod
The IHME weekly seminar kicked off for the quarter last week with Ver Bilano’s work on Estimation of recent trends in tobacco use and baseline projections to 2025. Ver used DisMod-MR extensively for this project, so I knew I was going to love it ahead of time.
I need a graphic for dismod that makes the point as nicely as this one:
It’s from P. Dierckx, Curve and Surface Fitting with Splines, which also has some pretty pictures of bivariate splines doing their thing:
I haven’t had time to write anything this week because I am up to my neck in this Seven-Samurai-style software engineering project. You know, where a bunch of untrained villagers (that’s me) need to defend themselves against marauding bandits (that’s the Global Burden of Disease 2005 Study), so they have to learn everything about being a samurai (that’s writing an actual application that people other than this one villager can use) as quickly as possible.
I guess this analogy is stretching so thin that you could chop it with Toshirō Mifune’s wooden sword. But, if anyone knows how a mild-mannered theoretical computer scientist can get a web-app built in two weeks, holler. If you prefer to explain in terms of wild-west gunslingers, that is fine.
Here’s my game plan so far: I’m going to make the lightest of light-weight Python/Django apps to hold all the Global Disease Data, and then try to get my epidemologist doctors to interact with it on the command-line via an interactive python session.
The rest of this post is basically a repeat of the Django tutorial, but specialized for building a data server for global population data. As far as interesting theoretical math stuff, hidden somewhere towards the end, I’ll do some interpolation with PyMC’s Gaussian Processes using the exotic (to me) Matérn covariance function. Continue reading
If you’ve read some of my previous posts, you might be wondering, what does Health Metrics have to do with sampling independent sets in graphs? (What is Health Metrics? you might also be wondering.)
In my new job, I’m not that interested in sampling independent sets. I’m mostly interested in sampling from a weird distribution that comes out of a Bayesian denoising problem.
Let me set the stage: a huge project that IHME is part of is the Global Burden of Disease study, which will (among other things) rank 200 diseases and injuries according to how severely they impact humanity. How you could possibly, ethically make this list is the topic of many books, and I won’t try to get into it now. IHME director Chris Murray seems to favor measuring impact in “disability adjusted life years” (DALYs), which is a fairly individualistic, fairly egalitarian approach.