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st: RE: Factor analysis(?) question - missing data


From   "Rodrigo Alfaro A." <ralfaro@bcentral.cl>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Factor analysis(?) question - missing data
Date   Tue, 22 Apr 2008 14:28:35 -0400

Glenn,

That sounds like you need the EM algorithm to recover the var-cov
matrix. You could do that if the set of variables are multivariate
normal distributed. There is a package, NORM, that is stand-alone for
Windows and it is available in Joe Schafer webpage. 

Also, you could "solve" you problem using multiple imputations. There is
a entry cost in the topic but you will see that is useful for many
cases. After the reading, you could use -ice- a package in Stata (by
Royston). With that you could manage your problem. 

Rodrigo.


-----Mensaje original-----
De: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] En nombre de Glenn Hoetker
Enviado el: Martes, 22 de Abril de 2008 02:07 p.m.
Para: statalist@hsphsun2.harvard.edu
Asunto: st: Factor analysis(?) question - missing data

Hi all.

This is perhaps more of a statistical questions than a Stata question.
My situation is this.  I have a large dataset in which there are 5-6
indicators each for a bunch of latent variables. Let me  
take as an example having 5 measures for innovative output, x1-x5.   
The problem is that very few observations have all 5 measures; some are
missing x1, some x2, etc. Almost every observation has at least 3
measures and most 4.

Is there anyway to optimally combine these indicators to measure the
underlying construct of innovative output that would use all available
measures for a given observation, i.e., x1-x4 for one observation, [x1-
x3,x5] for another, etc.  If I thought these were equally weighted, I
could just average over the available variables in each, setting aside
issues of measurement error.  However, I'm not convinced they are
equally weighted and would like to do this in a more rigorous fashion.

Any suggestions would be most welcome. Thanks in advance.

GPH


Glenn Hoetker
Associate Professor (Business, Law, Institute for Genomic Biology)
Resident Associate, Center for Advanced Study, Science and Technology in
the Pacific Century (STIP) initiative Faculty Fellow, Academy for
Entrepreneurial Leadership University of Illinois
217-265-4081
ghoetker@uiuc.edu
Personal website: www.business.uiuc.edu/ghoetker Science & Technology in
the Pacific Century initiative website: www.business.uiuc.edu/stip

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