Dear Mark,
See ?factanal for a factor-analysis function, in the standard stats package
(though factanal does ML factor analysis and not principal axes). Note that
help.search("factor analysis") turns this up.
With respect to your last question, it's not possible to know the source of
the difference without knowing what the difference is. A guess is that
specifying proportion=0.9 in SAS causes the program to use communality
estimates rather than 1's on the diagonal of the correlation matrix.
I hope this helps,
John
> -----Original Message-----
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Mark Strivens
> Sent: Thursday, September 09, 2004 7:26 PM
> To: [EMAIL PROTECTED]
> Subject: [R] R conversion
>
> I am a newcomer to R trying to convert a SAS program to R.
> Does anyone know if there is a functional equivalent of the
> SAS 'Factor' procedure?
>
> For example in SAS:
>
> proc factor DATA=cor method=principal rotate=varimax
> proportion=0.9 scree
>
> where 'cor' is a correlation matrix (as in the R 'cor' function)
>
> This should get you a list of eigen values as well as a
> factor pattern matrix.
>
> Also why when I use the 'eigen' function in R does it seem to
> give a subtly different answer to the eigen values generated
> by the above program?
>
> Many thanks for any help
>
> Mark Strivens
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