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Re: st: multiply imputed values for outcome


From   "Austin Nichols" <austinnichols@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: multiply imputed values for outcome
Date   Mon, 10 Jul 2006 20:48:26 -0400

Leslie--
If you used HLM, you may want -xtmixed- or -gllamm- (-ssc install
gllamm-) but I don't know about the "five plausible values" (for test
scores, right?).  But all those Raudenbush models can be re-written as
a single maximum likelihood model, right?

Maybe the answer to your question is in this list of references from
the help file for -gllamm- (or via email to sophiarh@berkeley.edu):

References (available from sophiarh@berkeley.edu)
----------
Rabe-Hesketh, S. and Skrondal, A. (2005). Multilevel and Longitudinal
Modeling using Stata. College Station, TX: Stata Press.

Rabe-Hesketh, S., Pickles, A. and Skrondal, S. (2004). GLLAMM Manual.
U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 160.
see http://www.bepress.com/ucbbiostat/paper160/

Rabe-Hesketh, S., Skrondal, A. and Pickles, A. (2005). Maximum
likelihood estimation of limited and discrete dependent variable
models with nested random effects. Journal of Econometrics 128,
301-323.

Rabe-Hesketh, S., Skrondal, A. and Pickles, A. (2002). Reliable
estimation of generalised linear mixed models using adaptive
quadrature. The Stata Journal 2, 1-21.

Rabe-Hesketh, S., Skrondal, A. and Pickles, A. (2004). Generalised
multilevel structural equation modelling. Psychometrika 69 , 167-190.

On 7/10/06, Leslie R Hinkson (lhinkson@Princeton.EDU)
<lhinkson@princeton.edu> wrote:
I have a data set that has multiply imputed values (5) for the outcome variable. I have previously used HLM software to conduct my analysis but I was told that with the new GLM features in Stata 9 that it should be possible to do the same in Stata. Unfortunately, I haven't found that way yet. Any thoughts? Also, is it possible to conduct standard linear regression analysis with multiple plausible values for the dependent variable using Stata 9?

Leslie
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