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From |
"Mona Mowafi" <mmowafi@hsph.harvard.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: Interpreting PCA output |

Date |
Thu, 24 Jul 2008 09:52:21 -0400 |

This is fantastic.. I will definitely take a look at your paper..Thank you! Just to be clear on the point you make re: dummy variables with the same factor; I follow F&P example in including multiple dummies with similar factor b/c in any case, each dummy is acting as a separate component in the analysis and is only explaining away a percentage of the total remaining variance, as I understand it. So there is no overlap between them in the procedure. I am not using a method for common variance (to identify factors) as you may (?) have indicated below.. Just thought I'd clarify... Again, many thanks... M. >>> "Stas Kolenikov" <skolenik@gmail.com> 7/24/2008 12:03 AM >>> Oh, that Filmer and Pritchett stuff. Take a look at our working paper -- http://www.cpc.unc.edu/measure/publications/pdf/wp-04-85.pdf. Typically the first component is the measure of wealth, while the next one or two are the measures of structure of that wealth (e.g. urban/rural difference, etc.). But in your case, you have dummy variables produces from the same factor (floor material, wall material, etc.), and they are negatively correlated. Rather than picking the common variation due to underlying wealth, the PCA now has to work on explaining those extra correlations. On Wed, Jul 23, 2008 at 1:55 PM, Mona Mowafi <mmowafi@hsph.harvard.edu> wrote: > Dear Statalisters, > > I'm new to the list and hope you will be able to help me with an analysis problem before me. > I have conducted a principal components analysis to identify principal components for 67 > underlying indicators or household asset. -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Interpreting PCA output***From:*"Mona Mowafi" <mmowafi@hsph.harvard.edu>

**Re: st: Interpreting PCA output***From:*"Stas Kolenikov" <skolenik@gmail.com>

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