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Hi Thanks for below. There is another layer of complexity. The covariates are scan-specific, and the covariate score exists for the first scan only. When prompted by SPM5 for the pair of covariate values, if one enters the covariate value for scan 1 and a zero for scan 2, this is inaccurate, as the model would use the difference (zero minus scan 1 covar value) as a change in score, which is not accurate, as the scan 1 value is the score at baseline not the change over time. Is there a way to enter the covariate value at time 1 when no value exists at time 2, in a manner that does not suggest that the time 1 value is a change over time? Thanks, Steve At 10:25 PM +0000 3/10/09, Jonathan Peelle wrote: >Hi Steve > >Are your covariates subject-specific, or scan specific? I.e. do you >enter the same number for the subject on both scan 1 and scan 2? With >a paired samples t-test, I think any part of your data that can be >explained in a subject-specific manner would be modeled out; so, if >your covariates are subject-specific, they aren't helping you explain >any more of your data. This would explain why your results are the >same. > >If your covariates aren't set up this way, then something else is >likely to be the culprit... > >Hope this helps, >Jonathan > >On Tue, Mar 10, 2009 at 8:22 PM, Steve Cramer <[log in to unmask]> wrote: >> I have scanned 24 subjects with fMRI twice per person. I am trying to >> examine a paired t-test while controlling for effects of two covariates. I >> am able to generate a paired t-test in SPM5 without the covariates, and the >> activation looks proper. >> >> However, the results (glass brain, cluster analysis) do not change when I >> add 1 or 2 covariates to the model. When I made the second model (paired >> t-test that has the two covariates), I used all the same choices (same >> pairs, no change in Grand mean scaling choices, etc) for the paired t-test, >> and note too that the covariates are entered without error (vector entered >> ok, variable named OK, no interactions, etc). In the second model (with 2 >> covariates), I entered a zero for both of these covariates in the contrast >> manager. >> >> Thus, it appears that in SPM5, a paired t-test with no covariates produces >> identical results as a paired t-test with 2 covariates properly specified. >> >> I would expect that the second model, with the two covariates that have a >> zero in contrast manager, would have a different result than the first >> model, with the difference reflecting removal of the signal accounted for by >> these two covariates. What am I missing, or doing wrong ? Thanks--Steve