Dealing with missing values in princomp (package "psych")

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf
Of Dimitri Liakhovitski
Sent: Wednesday, March 20, 2013 4:17 PM
To: Bert Gunter
Cc: r-help
Subject: Re: [R] Dealing with missing values in princomp (package "psych")

Yes, Bert, you are right and I do know I might run into a non-positive
definite intercorrelation matrix.
But if I do, then I can go back to those for whom I am doing the analysis
and tell them that. Not before.
This sad truth being said - can I do it directly in the function, without
building a intercorrelation matrix manually?
Thank you!
Dimitri

On Wed, Mar 20, 2013 at 7:04 PM, Bert Gunter <gunter.berton at gene.com> wrote:

Well, you can do this, but there's no guarantee that the resulting
correlation matrix will be positive definite. And what would principle
components based on this mean even if it is positive definite?

-- Bert

 On Wed, Mar 20, 2013 at 3:14 PM, Dimitri Liakhovitski <
dimitri.liakhovitski at 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

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--

Bert Gunter
Genentech Nonclinical Biostatistics

Internal Contact Info:
Phone: 467-7374
Website:

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--
Dimitri Liakhovitski

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