st: Factor analysis(?) question - missing data

[Glenn Hoetker <ghoetker@uiuc.edu>]

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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