Re: [Freesurfer] Qdec: regression with different numbers of variables

-log10(p) which p is the pvalue for the statistical test. The color is signed by the test.

On 08/19/2013 11:19 AM, ye tian wrote:

Dear Doug,

Would you please shine some light on what quantities are being plotted in those statistical maps of QDEC? Some linear combination of the columns of the design matrix?

Also, what is the "default" design matrix?

Thank you very much!

Sincerely, Ye

On Tue, Aug 13, 2013 at 11:45 PM, Douglas Greve <greve@nmr.mgh.harvard.edu mailto:greve@nmr.mgh.harvard.edu> wrote:

1 and 3 are the same model. Calling a variable a nuisance factor
is just a description. The model is actually
y  = age*meditation*b1 + meditation*b2 + err = y_hat + err

doug


On 8/13/13 6:12 PM, ye tian wrote:

...

Dear Freesurfers,

I am studying cortical thickness as a function of age
(continuous) and meditation practice (categorical, level1=Normal,
level2=TM). I have three separate cases of qdec, regression1,
regression2 and regression3.

Regression1: Discrete (Fixed Factor) = meditation; Continuous
(Covariate) = age
Regression2: Discrete (Fixed Factor) = meditation;
Regression3: Discrete (Fixed Factor) = meditation; Nuisance
Factor = age

For the question "Does the average thickness differ between
Normal and TM?", Regression1 and Regression3 have identical
result, which is different from Regression2, i.e., (1 = 3 !=2 ).
May I infer from this result the following about qdec:

1) Regression1 and Regression3 both fit cortical thickness,y, to
the model
    y  = b0 + age*b1 + meditation*b2 + err = y_hat + err
    Regression2 fits:
    y = b0 + b2*meditation + err = y_hat + err

2)  Some function of y_hat goes into the "average thickness",
hence the difference between 2 and the others.

However, what role does "Nuisance Factor" play in this case?

Thank you very much!

Sincerely,
Ye





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