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regression with uncertainty in both variables

On 15-Apr-99 Matthew Wiener wrote:
This really has nothing to do with R (I don't think, anyway -- could it be done
with lme?), but we do this kind of thing all the time using the HLM program
(Bryk, Raudenbush and Congden). At level 1, the outcome is the measure divided
by the standard error, and a series of dummies, one for each type of measure,
divided by the standard error. The level 1 variance is fixed at 1.0. These
1/s.e.,  come down to level 2, where they can be considered ``true score''
estimates of the measures, as outcomes, or as predictors, if you use  the
latent variable regression capability of HLM. I believe this capability is in
the latest version of the HLM program (maybe not -- we use a pre-release
version here), and the procedure should be detailed in the 2nd edition of Bryk
and Raudenbush, _Hierarchical Linear Models_, to be published (by Sage again?)
this summer or fall.

______________________________________________________________________
Stuart Luppescu         -=-=-  University of Chicago
ºÍʸ ¤ÈÃÒÆàÈþ¤ÎÉã(EUC)  -=-=-  s-luppescu at uchicago.edu
http://www.consortium-chicago.org/people/sl/sl.html
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