Sorry that I thought I answered your questions:
- Are Symptoms A and B: (a) actual symptoms that can be present, absent, or
graded into some scale, or (b) are these *sets* of symptoms (hence the
count)? This would clarify why in your design you have, in addition to the
count, there are two binary regressors.
=>They are symptom count of different sets of symptoms, not the actual symptoms. For example, symptom A is the number of depressed symptoms, and symptom B is the number of obsessive-compulsive symptoms. These two measures are not correlated with each other, at statistical level or at individual checklist content.
Please disregard my previous questions, now my question is can I use the following matrix and contrasts to test the differences of correlations (slopes) on FA with symptom A versus FA with symptom B, while controlling for other covariates? The scores in the following example will be demeaned.
SubjectID EV1 EV2 EV3 EV4
AllSub SymA SymB Covariate
Subject1 1 2 1 21
Subject2 1 0 3 25
Subject3 1 6 2 27
Subject4 1 1 7 45
Subject5 1 5 0 18
Subject6 1 0 1 35
Subject7 1 3 2 40
Subject8 1 2 0 22
Subject9 1 9 7 28
Subject10 1 1 4 37
Title Ev1 Ev2 EV3 EV4
C1 SlopeA>SlopeB 0 1 -1 0
C2 SlopeB>SlopeA 0 -1 1 0
Thank you for your help,
Date: Sun, 6 Aug 2017 20:03:43 -0300
From: "Anderson M. Winkler" <[log in to unmask]>
Subject: Re: Help with GLM for testing Correlation Difference (single-group repeated measures for TBSS)
Sorry but I still don't know whether A and B are symptoms or sets of
symptoms. Your later answers seem to contradict the earlier ones. Maybe you
could discuss with other people in your group the exact meaning of a
symptom and a set of symptoms, then reformulate the question...
All the best,
On 6 August 2017 at 15:29, Yuwen Hung <[log in to unmask]> wrote:
> Date: Sat, 5 Aug 2017 00:05:40 -0300
> From: "Anderson M. Winkler" <[log in to unmask]>
> Subject: Re: Help with GLM for testing Correlation Difference
> (single-group repeated measures for TBSS)
> Hi Yuwen,
> Could you give more details? In particular, could you clarify the
> - How many FA images each subject has? One or two? If just one, this
> doesn't need a repeated measures design?
> => Hi Anderson,
> Each subject only has 1 FA image, but each subject has two different types
> of symptoms (Symptom A and Symptom B).
> - What were the designs used for the analyses that lead to the different
> results for Symptom A and Symptom B? This helps to understand what
> dissociation you are talking about.
> => It was a simple correlation matrix ran between FA and Symptom A, and
> then ran again between FA and Symptom B, within the same group (with the
> same FA images).
> - Are Symptoms A and B: (a) actual symptoms that can be present, absent, or
> graded into some scale, or (b) are these *sets* of symptoms (hence the
> count)? This would clarify why in your design you have, in addition to the
> count, there are two binary regressors.
> =>They are symptom count only.
> - Can a given subject present symptoms A and B simultaneously? This also
> relates to the binary EVs in your design.
> =>Yes, any subject can present the two types of symptoms simultaneously.
> - Are these symptoms associated to some extent? (e.g., if A and B are sets
> of symptoms, are some of them, e.g., pain and nausea, present in both
> sets?) This wouldn't necessarily change the design, but might allow
> suggesting other approaches.
> =>Symptom A and B are different sets of symptoms and they are not
> correlated. None of the symptoms are present in both sets, and the symptom
> counts of A and B are not statistically correlated either.
Thank you very much for your help,