Just a small correction. I am running it like this:
mypc <- princomp(~.,data=q7a.forfa, cor=TRUE, na.action=na.omit)
With na.omit it works. But I have way too many unsystematically missing
values on different variables. I tried
na.action = na.pass, but it's not working:
Error in cov.wt(z) : 'x' must contain finite values only

Can it be that princomp does not allow pairwise deletion of misisng values?
Thank you!
Dimitri


On Wed, Mar 20, 2013 at 6:14 PM, Dimitri Liakhovitski <
dimitri.liakhovitski@gmail.com> wrote:

> Hello!
> I am running principle components analysis using princomp function in
> pacakge psych.
>
> mypc <- princomp(mydataforpc, cor=TRUE)
>
> Question: I'd like to use pairwise deletion of missing cases when
> correlations are calculated. I.e., I'd like to have a correlation between
> any 2 variables to be based on all cases that have valid values on both
> variables.
>
> What should my na.action be in this case?
>
> Thank you very much!
> --
> Dimitri Liakhovitski
>



-- 
Dimitri Liakhovitski

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