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From |
Cameron McIntosh <cnm100@hotmail.com> |

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

Subject |
RE: st: RE: Aren't distinct factors from factor analysis or PCA orthogonal to each other? |

Date |
Tue, 18 Aug 2009 08:31:58 -0400 |

Adrian,I think it would be a complete travesty to just feed that whole dataset into a factor analysis. Sure, it'll lump together variables with high correlations, but most of the time this doesn't reflect what's going on underneath the data (e.g., a web of diect and indirect causal relations that generated the observed associations/covariance matrix), and this type of situation is what tends to give factor analysis a "bad name" among statisticians. Factor analysis is typically only appropriate for reflective psychometric measures written specifically to assess an underlying trait (e.g., self-esteem, anxiety), not datasets like yours. I think there are probably complex causal relations among your variables that you should think hard about (using your theoretical knowledge about these variables)and maybe come up with a path-analytic model or growth curve model (say, GDP trajectory and its predictors). You could also compare models across countries.My two cents,Cam ---------------------------------------- > From: kokootchke@hotmail.com > To: statalist@hsphsun2.harvard.edu > Subject: RE: st: RE: Aren't distinct factors from factor analysis or PCA orthogonal to each other? > Date: Mon, 17 Aug 2009 17:15:33 -0400 > > Thank you to Cameron, Bob and everybody else for the references. > > I have a response to Jay and a couple more questions for everybody, if you can still help me... > > Jay wrote: >> Before you go any further I think you have a big problem to consider: 100 variables on, say 200 countries means you have WAY more covariances (or correlations) than you have countries. This means your correlation matrix is singular. > > > I don't think I have that problem because I don't have 200 countries. I only have about 30+ countries. > > However, even if I had 200 countries, I don't understand exactly what the problem would be because I have all 100 variables for country i and all 100 variables for country j stacked on one another. So, I have: > > country year GDP inflation reserves > Argentina 1990 2.3 6.4 100 > Argentina 1991 2.8 7.4 250 > Argentina 1992 2.6 7.0 200 > ... > Argentina 2006 3.2 8.0 400 > Brazil 1990 1.7 5.4 120 > Brazil 1991 2.1 6.3 140 > Brazil 1992 2.5 7.0 180 > ... > > > So the variables I enter into my factor analysis are GDP, inflation, and reserves... and so the -factor- command in Stata knows nothing about the panel/time-series structure of my data. I can see why it should be relevant to account for the underlying panel structure of the data -- for instance, that jump in GDP/inflation/reserves and any other variables between Argentina in 2006 and Brazil in 1990 may be a bit strange to account for. > > So, the first question is: do I need to take this panel structure into account? And if so, how? > > The other question is, do units matter? For instance, I know that factor analysis or PCA are all based on a variance-covariance matrix... but if I have two variables, x and y, and I take the covariance between the two of them, that'll be different than if I take the covariance of, say 2x and y: > > cov(x,y) <> cov(2x,y) > > and so what would happen if I express my GDP in dollars for all countries or in local-currency units?? Or in millions or in billions??? > > > Thank you once again. > > Best, > Adrian > > > > > _________________________________________________________________ > Hotmail® is up to 70% faster. Now good news travels really fast. > http://windowslive.com/online/hotmail?ocid=PID23391::T:WLMTAGL:ON:WL:en-US:WM_HYGN_faster:082009 > * > * 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/ _________________________________________________________________ More storage. Better anti-spam and antivirus protection. Hotmail makes it simple. http://go.microsoft.com/?linkid=9671357 * * 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/

**Follow-Ups**:**RE: st: RE: Aren't distinct factors from factor analysis or PCA orthogonal to each other?***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**References**:**st: Aren't distinct factors from factor analysis or PCA orthogonal to each other?***From:*kokootchke <kokootchke@hotmail.com>

**st: RE: Aren't distinct factors from factor analysis or PCA orthogonal to each other?***From:*"Verkuilen, Jay" <JVerkuilen@gc.cuny.edu>

**RE: st: RE: Aren't distinct factors from factor analysis or PCA orthogonal to each other?***From:*kokootchke <kokootchke@hotmail.com>

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