Re: basic que-Factor Analysis

Posted by Mehul Pajwani on Aug 17, 2011; 5:06pm
URL: http://spssx-discussion.165.s1.nabble.com/basic-que-Factor-Analysis-tp4706531p4709104.html

by first three que, I am referring to R Factor Analysis (grouping variables) and once I am done with that, I intend to use those composite variables for cluster analysis.

 

Thanks,

 

Mehul

On Wed, Aug 17, 2011 at 11:22 AM, Art Kendall <[hidden email]> wrote:

Do you mean Q Factor analysis  which is an old way of clustering cases?

Art Kendall
Social Research Consultants

On 8/16/2011 10:16 PM, Mehul Pajwani wrote:

Hi,

I am trying to run (for the first time) factor analysis in SPSS.18 and
would appreciate any feedback and recommendations from seasoned SPSS
users and statisticians on the following

I started with 93 continuous variables (5-point, 6-point and 7-point
rating scale type questions) and trying to reach to a reasonable
factor solution. Here are key questions I am struggling with.

1) I started with 93 variables. Are these too many variables to start
with? Is there any guideline about (minimum and maximum) number of
variables?

2) Though all variables I am using are continuous (rating scale) they
are of different scale points and types (e.g. 5-point ratings where
1=Strongly Disagree and 5=Strongly Agree; 6-point scale where 1=Will
not influence at all and 6=Will strongly influence etc.).  I
understand that this will have very different variance and therefore
can possible affect the results. Having said that do I need to
standardize these variables or factors analysis will automatically
take care of it?

3) I selected an option for Rotated Component Matrix but it failed to
produce that with the message “Rotation failed to converge in 25
iterations. (Convergence = .001).” Surprisingly, I ran the factor
analysis with the same data couple days before (with 92 variables, I
guess) and it did produce Rotated Component Matrix.  Any thoughts on
why it is showing that error and how to handle this?

4) My ultimate goal is to identify broader dimensions based on factor
analysis and then use these composite variables for the segmentation
by doing cluster analysis. Is this the right approach for the
segmentation?

I would appreciate any help on this.

Regards,

Mehul

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