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Re: st: Constructing socio-economic status scale using Principal Components Analysis


From   Maarten Buis <maartenlbuis@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Constructing socio-economic status scale using Principal Components Analysis
Date   Wed, 28 Nov 2012 10:18:06 +0100

On Wed, Nov 28, 2012 at 3:59 AM, Ameya Bondre wrote:
> I have a data-set with about 37 variables that can assess household
> socio-economic status in a sample of about 6000 households. These
> include variables measuring household wealth, access to water and
> sanitation, rural households owning animals, etc.
>
> I used factor analysis (factor var1, var2, ...., pcf)

I would say that factor analysis is incorrect for this problem. Factor
analysis assumes that the latent concepts influence the observed
variables. This makes sense for something like an intelligence test:
someone is more or less smart (the latent variable) and that
influences the probability of answering a set of questions correctly
(the observed variables). Conceptually, socio-economic status is just
a pool of resources available to a person, family, or household: so it
is the number and kind of animals, the wealth, a house with a concrete
floor, etc. (the observed variables) that influence, or add up to, the
socio-economic status (the latent variable).

Some of the possible solutions available in Stata are discussed here:
<http://www.maartenbuis.nl/wp/prop.html>.

Hope this helps,
Maarten

---------------------------------
Maarten L. Buis
WZB
Reichpietschufer 50
10785 Berlin
Germany

http://www.maartenbuis.nl
---------------------------------
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