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Topic: Principal Component Analysis Alternatives for low sample to
dimensions ratio

Replies: 5   Last Post: Apr 11, 2013 11:26 PM

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Art Kendall

Posts: 200
Registered: 12/7/04
Re: Principal Component Analysis Alternatives for low sample to dimensions

Posted: Apr 11, 2013 7:18 AM
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Please describe you data in more detail.
What are your 2000 variables? Are they some form of repeated measure
such as items in summative scales, the same variable measured at
different times or at different points along a spectrum?

What are you cases?

What questions do you want to answer with the data?

Art Kendall
Social Research Consultants

On 4/10/2013 11:44 PM, Krevin wrote:
> Anyone know of good alternative methods to PCA when you have too many dimensions compared to samples?
> If I have 2000 variables and 300 samples, I cannot properly use PCA.
> I'm looking for something that can minimize false positive separation of sample points without needing to reduce my number of variables.
> Thanks,
> Krevin

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