(1) With a limited number of subjects, there isn't much you can do other than analyze subjects with complete data.

(2) The issue with looking at the correlation for all subjects at T1 versus the 12 subjects at T3 is that the correlation may not change, but could be different in the subjects that came back, so you are limited to the 12 subjects.

If you had many more subjects, there are more advanced statistical models that you could use that allow for missing data at later timepoints (e.g. mixed-efffect models and parallel growth models).


Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Postdoctoral Research Fellow, GRECC, Bedford VA
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
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On Tue, May 26, 2015 at 11:20 PM, Sharlene Newman <[log in to unmask]> wrote:
SPM users:

We are in need of help.

We have recently conducted a longitudinal fMRI study in which we collected three time points. There was an uneven number of participants per time point, such that we went from 35 to 25 to 12 subjects (which means we have 12 subjects that came back for all 3 sessions, but several others attrited).

We have two questions:
1) Is there an analysis technique that we can use to compare activation using all of the subjects (including the attrited ones)? Currently we have analyzed the data with just the 12 subjects using paired t-tests between the time points.

2) More importantly, we are interested in correlating individual differences measures with activation across time. For instance, we collected Stroop data. We want to see how the correlations with their Stroop performance changed over time, including all subjects and not just the 12 that came back all three time points.

Any advice here will be greatly appreciated.  Thanks.

Sharlene