I am running a small study in which both treatment (n = 7) and control groups (n= 6) have undertaken the same 48 item rating scale task (scale = 1 - 10) pre- and post-treatment period. We are running an independent t test to see whether the mean difference score (post test score - pre test score) for the treatment group were significanly larger than for the control group.

Rather than running the t-test on the mean difference scores for each particpant (this provides only 7 vs. 6 data points), I am considering whether to run a t-test on all all differnce scores collected. This would give me 336 (7 x 48) for the treatment group and 288 (6 x 48) data points for the respective group. I could then run an analysis that is more robust to violations of t-test assumptions (non-normality, unequal variances, unequal group sizes etc), and of course run robust checks for these vilations.

However, I am unsure if this is a correct way to go about the analysis, given that in SPSS I will have more than one score per particpant in the same column. So my question is: Can I run the analsysis on all difference scores, rather than the mean difference scores for each participant?

Any advice would be much appreciated.