Dear Dr. McLaren,
Thanks for your reply. For model (3), are the following design and contrast correct?
2 sample t-test with 2 covariate columns:
scan for group1: 1 1 1 1 1 0 0 0 0 0
scan for group2: 0 0 0 0 0 1 1 1 1 1
Q1 for group1: 3 4 1 2 3 0 0 0 0 0
Q1 for group2: 0 0 0 0 0 8 6 9 7 5
contrast for common correlation between groups: 0 0 1 1
contrast for different correlations between groups: 0 0 1 -1 or 0 0 -1 1
I have a further question: what does this contrast, 1 -1 0 0, mean? Does it mean group1>group2 while ignoring the Q1 scores in both groups? For the Q1 scores differ significantly in both groups in my case, is it an inappropriate contrast to look at since the assumption of ANCOVA is violated...?
Thanks again and Merry Christmas!
Best wishes,
Meikei
________________________________________
From: MCLAREN, Donald [[log in to unmask]]
Sent: Saturday, December 24, 2011 2:08 AM
To: mmkleung
Cc: [log in to unmask]
Subject: Re: [SPM] correlation in 1 group or both groups of subjects?
There are a number of options:
(1) Do the analysis separately for each group.
(2) Use a two-sample t-test with a single covariate (assumes same slope with your covariate across groups)
(3) Use a two-sample t-test with 2 covariates (one for each group; allows for a separate slope in each group).
Depending on what your trying to show you can choose model (2) or (3). Model 3 will have slightly better results as the error will be lower if the slopes are slightly, but not significantly different. With model (3), you can test the average slope. It has the advantage that the results will not be skewed by group size differences.
Hope this helps.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
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On Fri, Dec 23, 2011 at 10:58 AM, mmkleung <[log in to unmask]<mailto:[log in to unmask]>> wrote:
Dear all,
I'm studying the relationship between grey matter volume (GMV) and questionnaire scores (Q1, Q2, Q3, Q4). I have two groups of subjects (all are healthy subjects), whose GMV differ in some regions as revealed by VBM. They also differ in Q1, Q2 and Q3. Then I extracted the mean GMV values out from these regions of all subjects. I found two sig. negative correlations between: GMV values and Q1, GMV values and Q2. However, these correlations were not found when the analysis is done on each group of subjects separately.
Is there any problem to look at the above relationship in all subjects (for the sake of power), but provided that the 2 groups of subjects have sig. group difference in GMV in these regions and Q1-3?
Thanks for your advice!
Best wishes,
Meikei
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