The reason for  my asking is because I have to replicate the same analysis
done in SPSS and SAS.

Again, to make it clear - it's respondent-weighted Factor Analysis with a
desired number of factors. Method of extraction: Principal Components.
Rotation: Varimax.

The only solution I can think of is to multiply my respondent weight by 10
(or by 100) and round it so that the new "weight" has no decimals, then
repeat every row as many times as the new weight says and run regular,
unweighted "principal" on the new data. I've done it - but again, this does
not match the Factor Scores from SPSS and SAS exactly.

Any other ideas?
Thank you!


On Thu, Apr 25, 2013 at 9:21 AM, Dimitri Liakhovitski <
dimitri.liakhovitski@gmail.com> wrote:

> Hello!
>
> I am doing Principle Componenets Analysis using "psych" package:
>
> mypc<-principal(mydata,5,scores=TRUE)
>
> However, I was asked to run a case-weighted PCA - using an individual
> weight for each case.
>
> I could use "corr" from "boot" package to calculate the case-weighed
> intercorrelation matrix. But if I use the intercorrelation matrix as input
> (instead of the raw data), I am not going to get factor scores, which I do
> need to get.
>
> Any advice?
> Thank you very much!
>
> --
> Dimitri Liakhovitski
>



-- 
Dimitri Liakhovitski

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