Illustrative datasets and analysis for multilevel modelling I recently took an introductory course on multilevel modelling. Most of the datasets and examples we used were from the social sciences. I've just got a 2 week internship in a biostatistics department, where they want me to start a project concerning the variation at hospital level of patient outcomes for an emergency condition that has a high mortality rate, both between hospitals and over a 5 year time span. I'm starting the internship next week, and I was hoping to find a book or online resource where a similar analysis (preferably with R, Stata or MLwiN) has been done, preferably one where they provide their data sets for the reader. Any links would be most welcome.
Edit: I will be working with a dataset detailing all recorded aspects of the patient's in-hospital care. The main outcome of interest is death within 30 days of admission.
 A: You might want to check out the UCLA multilevel modelling resources.
For example, the UCLA site has


*

*this page that includes datafiles and analysis for several examples from Snijders and Bosker using multiple analysis packages.

*This copy of Harvey Goldstein's multilevel modelling text with data files
A: Are you aware of the online resources at the MLwiN site? In particular their free online course. They go through examples in all three software packages you mention (R, Stata, and MLwiN of course), and provide datasets along with them. 
One of the modules goes through multi-level models for binary responses, which it sounds like your project would entail.
Currently our mixed-model tag wiki has the community suggested readings for multi-level models. Although I couldn't say off-hand which of those books had accompanying data.
A: Stata comes with a bunch of toy data sets that you can take a look at: File -> Example Data Sets -> Manual datasets -> [XT] -> there appears to be some biostat data under xtmepoisson and xtmixed. There are some examples on GLLAMM website with both code and data: http://gllamm.org/examples.html.
