-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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