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Re: st: PCA with Missing Values (or other factor analysis)
From
Stas Kolenikov <[email protected]>
To
[email protected]
Subject
Re: st: PCA with Missing Values (or other factor analysis)
Date
Wed, 6 Jul 2011 11:18:41 -0500
Since you have binary data, PCA is totally inappropriate. You could
use -xtmelogit- or -gllamm- in the context of cross-classified data
(both programs are designed to work with nested data, so working with
the data like yours requires certain data management and estimation
tricks).
On Sat, Jul 2, 2011 at 11:13 PM, Nick Eubank <[email protected]> wrote:
> Hello All,
>
> I'm trying to do a PCA on legislator votes (1 or 0), where different
> legislators have overlapping but distinct terms. In other words,
> legislator A is in office periods 1 and 2, legislator B is in office 2
> and 3, so A has no votes in period 3 and B has no votes in period A. I
> want to map their "ideal points" (i.e. pca predicted value from votes)
> into the same space. But PCA obviously dislikes missing values.
>
> Suggestion? I'm really open to any factor analysis algorithm.
>
> Thanks!
>
> Nick
>
>
>
> --
> PhD Student, Political Economics
> Stanford University GSB
> [email protected]
> Cell: +1 (303) 918.6528
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--
Stas Kolenikov, also found at http://stas.kolenikov.name
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