 |
 |
raghu venkatra wrote: > Hello SPMers, > > I ran a paired t test on a 4-subject study. The data I have consists of two > scans per subject (drug/vehicle). I chose the PET population main effect > (paired t test). The null hypothesis I believe I am testing is that the > drug has no effect. I used a [1,-1] contrast for increase in metabolism and > [-1,1] for decrease in metabolism. > I am confused as to if I am doing a model analysis here, and will have to > use the two contrast images for a second level analysis using the basic > model two-sample t test. > I would recommend that you don't do a 2nd-level analysis (ie. a random effect analysis) with this data because you don't have enough subjects. > Some questions: > *Do the SPM_T*.img maps indicate increase/decrease in metabolism for the > contrats? Yes. [1 -1] would be relative increase in metabolism due to drug. Usually you'd do a [1 -1] contrast for each subject at the first level and then do a one sample t-test at the 2nd. But with 4 subjects this gives you only 3 degrees of freedom which is'nt enough. > *If I do perform a second level analysis, two sample t test on the con*.img > images, for the above two contrasts, what is the null hypothesis? The null hypothesis would be that, in the population at large, there is no difference in activation between the two conditions. > *in general does first level analysis, maps basically an analysis of the > estimated model? I would recommend just analysing each subject separately and reporting the results as a series of case studies (unless you can get data on another 8 subjects). So 'at the first level' you plot maps of regions where you can reject the null hypothesis: In subject X at location y there is no difference in activation between the two conditions. Hope this helps, Will. > > > Thank you in advance. > Raghu Venkatram > > > -- William D. Penny Wellcome Department of Imaging Neuroscience University College London 12 Queen Square London WC1N 3BG Tel: 020 7833 7478 FAX: 020 7813 1420 Email: [log in to unmask] URL: http://www.fil.ion.ucl.ac.uk/~wpenny/