My guess is that the regressors for the easy are roughly 3x smaller
than for the hard (as you have modelled them for 1s instead of 3).
This means that, for the same effect size, the copes will be 3x higher
and the varcopes 9x higher.
T
On 17 Feb 2010, at 18:55, Todd Thompson wrote:
> Hi, all. I apologize if this is a dumb question, but I'm having
> trouble trouble-shooting something:
>
> I have a simple slow event-related design:
> 1) display a hard problem to the subject -- usually around 3s, but
> variable from 1s to 15s.
> 2) let them take their time solving it
> 3) wait 12s for ITI
> 4) display an easy problem to the subject
> 5) let them take their time solving it -- consistently less than 1s
> 6) wait 12s for ITI
>
> (repeat for 600s)
>
>
> When I analyze my data, I set up two regressors (easy/hard), each with
> a 3-column timing file with the subject's RTs for that problem type as
> the durations.
>
> My contrasts have unexpected stats, and in trying to track down why, I
> discovered that the values in the varcopes for the easy (faster)
> events are hugely higher than the varcopes for the hard (slower)
> events. This is true for every one of six different subjects. Is this
> expected? If so, can anyone explain it to me? If anything, I was
> expecting the opposite, since the responses to easy trials are more
> uniform than the responses to the harder trials. (For what it's worth,
> there doesn't seem to be a difference in stimulus-correlated motion
> between my two conditions...)
>
> Thanks!
> Todd
>
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