Sender: |
|
Date: |
Mon, 11 Nov 2002 11:36:40 -0500 |
Reply-To: |
|
Subject: |
|
MIME-Version: |
1.0 |
Content-Transfer-Encoding: |
8bit |
Content-Type: |
text/plain; charset=iso-8859-1 |
From: |
|
Comments: |
|
Parts/Attachments: |
|
|
if you are using SPSS and are familiar with it I would suggest the following for such a small set of samples. First, from your email you imply you have two sample sets ergo to symetric matrices. I recommend the folowing which all can be done in SPSS:
1) reduce the two matrices using principal components. Make sure have the same number of eigenvectors produced.
2) rotate the resulting PCA of one set onto the other using a Promax rotation. You have map each matrix into the same coordinate space.
3) after the rotation and/or the PCA you can see the RSquare the fit of one matrix on the other.
SPSS with small samples as your works dandy!
N Gottlieb
ProfileDepot, Inc.
you wrote:
Hi All,
I am a doctoral candidate studying in the UK. As part of my research, I use card sorting tasks to investigate underlying cognitive structures of prospective teachers within a subject domain. The result of this card sorting task is a symmetrical matrix with 56 rows and 56 columns. What I want to do is to correlate two matrices which represents an expert's categorisation of the cars and a subject's categorisation. Here I have the problem. I do not know how to do this. Can you help me in solving my problem? I am reasonably familiar with SPSS. Is it possible to do this with SPSS? Or do I need another program?
Thank you very much for your interest and time.
Ufuk YILDIRIM
|
|
|