Dear Doug,

Thank you very much!

Sincerely,
Ye


On Tue, Sep 3, 2013 at 5:29 PM, Douglas N Greve <greve@nmr.mgh.harvard.edu> wrote:
Yes, that is correct for DODS. For DOSS, it is y = e + bi*xi + ci*zi
doug


On 09/03/2013 01:03 PM, ye tian wrote:
Dear Doug,

Would you please let me know what the general formula for the model is for discrete variables x1, x2, .... , xN, covarying with continuous variables z1, z2, ..., zM?
Is it

y = error + bi*xi + cij*xi*zj ?

Otherwise, how does freesurfer decide what model to use?

Thank you very much!

Sincerely,
Ye


On Mon, Aug 19, 2013 at 11:26 AM, Douglas N Greve <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> wrote:


    QDEC creates a sentence that describes each contrast. Is that
    sentence not clear? I think the only other docs we have for QDEC
    are the tutorial.
    doug






    On 08/19/2013 12:19 PM, ye tian wrote:

        Dear Doug,

        If I only have two groups, does the statistical test reduce to
        a two-tail t-test?

        Sorry, I meant to ask what the "default" contrast is, meaning
        what the contrast is when I specify no nuisance factor?

        Is there an official document where the QDEC setup is gone
        over systematically?

        Thank you very much!

        Sincerely,
        Ye


        On Mon, Aug 19, 2013 at 11:04 AM, Douglas N Greve
        <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>
        <mailto:greve@nmr.mgh.harvard.edu
        <mailto:greve@nmr.mgh.harvard.edu>>> wrote:


            -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>
        <mailto:greve@nmr.mgh.harvard.edu
        <mailto:greve@nmr.mgh.harvard.edu>>
                <mailto:greve@nmr.mgh.harvard.edu
        <mailto:greve@nmr.mgh.harvard.edu>

                <mailto: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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