Sorry, there are two separate issues: the data itself (which is a big dataset where they following a big set of nurses for many years, and recorded lots of things about them), and how the data could be used to maybe get causal conclusions.

Plenty of folks at Harvard (e.g. Miguel Hernan, Jamie Robins) used this data in a sensible way to account for confounding (naturally their results are relatively low on the 'hierarchy of evidence', but still!) Trying to draw causal conclusions from observational data is 95% of modern causal inference!

Open thread, January 25- February 1

by NancyLebovitz 1 min read25th Jan 2014318 comments

8


If it's worth saying, but not worth its own post (even in Discussion), then it goes here.