> What accounts for the difference?
You're seeing the differences because of the respective null hypotheses those two tests are constructed against. The null hypothesis for the first test is
H_0: stim1 + stim2 = 0
and the second is
H_0: stim1 = 0 and stim2 = 0
> Essentially, we want to obtain a Full F, parameter estimate and corresponding
> t-value for the contribution of both stim1 and stim2. Scenario 1 appears to be
> what we want, no?
The phrase of "the contribution of both stim1 and stim2" is very vague. The first test of yours looks for the combined (or average) effect of the two stimuli (its t- and F-statistic are essentially the same thing), while the second test (F-statistic) gives you the effect from either of the two (i.e., when the null hypothesis gets rejected), but does not differentiate between them. In addition, 3dDeconvolve also provides the individual effect significance (t-statistic) for each of the two stimuli in the second test, which are just duplicates for the two regression coefficients in this case. To me the second test is usually much more informative and interpretable than the first one, but there are exceptions (e.g., when testing for main effect).
Gang
Edited 5 time(s). Last edit at 07/19/2012 07:49PM by Gang.