Hi Shady,
Try assembling the design as this:
EV1: Group 1 (coded as 0/1) EV2: Group 2 (coded as 0/1) EV3: Group 3 (coded as 0/1) EV4: Sex (coded as +1/-1) EV5: Site (coded as +1/-1)
The contrasts to compare the three groups are then: C1: [1 -1 0 0 0] C2: [1 0 -1 0 0] C3: [0 1 -1 0 0] C4: [-1 1 0 0 0] C5: [-1 0 1 0 0] C6: [0 -1 1 0 0]
From the description it seems site and group are confounded, although not
completely, such that it should be possible to still draw some inferences, although without much power.
The above does not include terms for interactions. If it's something you could be interested in, then extra EVs can be added.
All the best,
Anderson
On 30 August 2016 at 11:40, Shady Rahayel shady.rahayel@gmail.com wrote:
Greetings,
I want to design a matrix that contains 3 fixed factors. The first is diagnosis (3 levels), the second is gender (2 levels), and the last is imaging site (2 levels). However, the thing is that the imaging site factor only applies to only one level of the diagnosis factor (i.e. patients from the first level of the diagnosis factor were seen in 2 different imaging sites, whereas for the two other groups of patients the same imaging site was used).
I have followed the tutorials but I still be am confused concerning how I should go about creating the design matrix with 3 fixed factors. Would it be:
GroupDescriptorFile 1 Title xx Class Diagnosis1-Male-Site1 Class Diagnosis1-Female-Site1 Class Diagnosis1-Male-Site2 Class Diagnosis1-Female-Site2 Class Diagnosis2-Male-Site1 Class Diagnosis2-Female-Site1 Class Diagnosis3-Male-Site1 Class Diagnosis3-Female-Site1 Input etc etc...
Afterwards, if I'm looking for a difference between Diagnosis1 and Diagnosis2, what would be the contrast? 0.25 0.25 0.25 0.25 -0.5 0.5 0 0 ?
Thank you very much for your help,
Shady
-- *Shady Rahayel* Étudiant au Ph.D. en neuropsychologie R/I Université du Québec à Montréal
Centre d'Études Avancées en Médecine du Sommeil Hôpital du Sacré-Coeur de Montréal
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