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| From | "Nick Cox" <n.j.cox@durham.ac.uk> |
| To | <statalist@hsphsun2.harvard.edu> |
| Subject | RE: st: Unbalanced repeated measures analysis question |
| Date | Thu, 22 Jul 2010 17:50:20 +0100 |
HLM in this context usually means hierarchical linear model[l]ing. Nick n.j.cox@durham.ac.uk Ploutz-Snyder, Robert You could define your model the way you suggested, yes, however mixed models can be specified a number of different ways depending on your research goals and how you want to consider the nesting of your repeated measures factors (i.e. random terms). There are a number of excellent books on this type of analysis, going by names including mixed-effects modeling, mixed modeling, higher level modeling (HLM), multi-level modeling (MLM) and probably a few other terms... If you are interested in a more Applied book that uses Stata in particular, Rabe-Hesketh and Skrondal put together a nice one book called Multilevel and Longitudinal Modeling Using Stata. I think you might do well to take a course in MLM if you can to at least wrap your brain around the theory. But if you want to jump right in then a book like this one could get you going in the right direction. Karin Jensen Thanks to Robert and David for your helpful comments. Sorry to sound stupid here but mixed models are entirely new to me. I have been reading up on them. I have the variables outlined below: SubjectID MeasurerID MeasurerType Result GoldStandard where MeasurerID is always a certain MeasurerType (1-3) SubjectID and MeasurerID should be random effects and MeasurerType fixed? How would you specify that in the xtmixed syntax? I am confused about having two grouping variables for the random effects. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/