If I understand you, you want to identify regions where OLD and YOUNG
are different. I assume there is only 1 image per subject for the
A) use 6 groups in a one-way ANOVA, then create an old/young contrast.
This means that each cohort will have a different mean and variance
that is unaffected by the other groups.
B) if there are young and old from the same cohort of subjects, then I
would have a variable for age group and variables for cohort. Then the
contrast would be between the age group variables. The cohort variable
is then just an extra term that reduces the variance.
Personally, I like model A better as it doesn't infer that the cohort
effect has to be same across the age groups as model B assumes.
If you have repeated measures, subtract then you can only look at the
age*measure interaction since main effects of group aren't valid in
Let me know if you have any questions.
On Friday, May 20, 2011, Jason Steffener <[log in to unmask]> wrote:
> Hello all,
> I have data from 6 different "cohorts" that I would like to analysis
> in one big group analysis.
> I have two age groups (yng and old). The yng data are from 4 separate
> studies and the old are from 2 separate studies.
> The data were collected in "chunks" over a couple of years. So 20
> young here, then another 20 young the following year etc. Although,
> the training and task were the same I want to account for the fact
> that the data were not collected continuously.
> My interest is in age differences and want to make sure that I account
> for any "cohort" effects so I can correctly interpret any age group
> Based on box-plots of the behavioral data there is evidence of cohort effects.
> Thank you for any guidance,
> Jason Steffener, Ph.D.
> Department of Neurology
> Columbia University
Best Regards, Donald McLaren
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
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