I ran a first level PPI on a cohort of subjects, and generated beta-weights for the PPI terms (one PPI term for each task condition). I then threw the PPI beta weights into a group analysis using 3dLME and got some interesting results. However, when I dig into it, I find that many of the significant effects from 3dLME seem to be driven by a few outlier subjects with wildly high or low PPI beta weights.

- Any advice on how to interpret beta weights of an interaction term?
- Should I be taking the square-root of PPI beta weights on individuals before I throw them into a group analysis?

(My thought is that the PPI beta weights are sort of "squared" because they are fit with covariates that are formed by essentially multiplying two other covariates together. Would square-rooting the PPI beta weight help "level the playing field" across subjects? How would I handle negative values?)