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 >