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 <gr...@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 <
>> gr...@nmr.mgh.harvard.edu 
>> <mailto:gr...@nmr.mgh.harvard.**edu<gr...@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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> Douglas N. Greve, Ph.D.
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