Hi Peter, thanks.

After reducing the data to seven factors, these go into a regression model to predict a continuous outcome.

I'm not familiar with proc pls -- any info on that?

Funny that you should mention MI and MIANALYZE--I'm also investigating that for the missing data issue within this dataset.

Julia -----Original Message----- From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of Peter Flom Sent: Thursday, May 10, 2007 11:51 AM To: SAS-L@LISTSERV.UGA.EDU Subject: Re: variable reduction (proc factor) with repeated measures

Julia Rushing <jrushing@BELLOMYRESEARCH.COM> wrote

I'm working on a study with multiple variables that we are running through PROC FACTOR (method=princomp) to reduce the highly correlated variables down to a subset of factors (21 vars were reduced to 7 factors).

The respondents in the dataset have from 1 to 5 records depending on how many products they rated. Responses within respondent should be correlated. So far we've done the factor method ignoring this issue. I wonder what techniques are available to take this within-person correlation into account while or before doing the factor analysis. Perhaps results would not differ. >>>>

Several thoughts: 1) What is the purpose of the data reduction? Is it for some kind of regression model? If so, what kind?

2) Have you considered PROC PLS instead of reducing the data this way?

3) If you decide that reducing the data this way is the right thing to do, PROC MI and PROC MIANALYZE may be helpful

and I hope this was helpful....but if you provide more context, more helpful help may happen (please respond to SAS-L, not just me)

Peter