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RE: st: Unbalanced repeated measures analysis question


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.


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