The following post might prove helpful:
http://www.stata.com/statalist/archive/2007-12/msg00504.html
The short version: -findit ice-
Hope this helps,
Maarten
--- Glenn Hoetker <[email protected]> wrote:
> 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.
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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