Print

Print


Thanks for your reply. Are there ways to remedy some of the problems you mentioned?

-Drew

From: MCLAREN, Donald [[log in to unmask]]
Sent: Thursday, December 12, 2013 9:32 PM
To: Sevel,Landrew S
Cc: SPM
Subject: Re: [SPM] Flexible Factorial Warning

I don't think you've made an error - although its possible as you haven't provided your design matrix. The design matrix is not invertible, has no unique solution and thus is badly scaled. 

You should only include subjects that have complete data. While SPM will let you enter incomplete data, no one seems have rigorously tested the impacts missing data. In theory, missing data should not be a problem. However, I wouldn't risk doing something with unknown consequences.

Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Postdoctoral Research Fellow, GRECC, Bedford VA
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.


On Thu, Dec 12, 2013 at 1:08 PM, Sevel,Landrew S <[log in to unmask]> wrote:
Hello all,

I have a flexible factorial design question/concern. I received the following warning when running a model:

Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.869573e-18. 

The design has subject (N=42), Group (2), session (3), and condition (2) factors

I used the subject option and specified the following conditions per subject
1 1 1
1 2 1
1 3 1
1 1 2
1 2 2 
1 3 2
… For group one and
2 1  1 
2 2 1 
2 3 1
2 1 2
2 2 2
2 3 2
… for group 2

Have I made an error somewhere?

Additionally, am I correct that all subjects need the same amount of data (I.e. I could not include a subject with only 2 sessions)?

Many thanks,

Drew