On Fri, Jul 17, 2009 at 2:11 AM, Christopher
Benjamin<[log in to unmask]> wrote:
> Hi, I'm modelling a task in which participants perform the same cognitive task on a number
> of stimuli which differ only in their color. I'm having trouble working out the best way to
> model this and would love feedback.
> I have stimuli of four different colors, with responses to each color split into correct and
> incorrect responses.
What question are you interested in asking of the data? That will be
helpful in informing your choice of model.
> A. If I consider modelling the process and then the color separately [i.e., regressors (1)
> correct, (2) incorrect, (3-6) color], I think I'm likely to end up with a degenerate design.
In this setup, the first regressor will model the activity in common
across all correct trials, regardless of what color items were
presented in. The color regressors, in this model, would then tell
you how activity associated with each color differed from the common
activity modeled by regressor 1.
Note that as you have it here the color regressors will pick up
activity for both correct and incorrect trials, which may not be what
you want....you might want to split the colors by correct/incorrect.
> B. If I model correct and incorrect responses by color [(1)blue-correct, (2)blue-incorrect,
> (3)purple-correct...(8)] it seems intuitively wrong - I'm splitting variance for a cognitive
> process that is almost identical between four different regressors (for both correct and
> incorrect responses). I also think I lose a lot of power in each regressor's estimate.
On the one hand you are correct, in that, assuming that blue-correct
and purple-correct share a lot of activity, you're splitting up a
single process, and giving yourself less data for each regressor.
However, note that in this case, doing a contrast across several
columns of your design matrix (i.e. the four columns coding for
correct responses) should give you the same answer (i.e. the average
activation for this process) as approach A above. The only caveat
would be if the number of correct/incorrect trials differs much as a
function of color, then you will get slightly different weightings
depending on which approach you take.
Hope this helps,