I want to compare beta weights across different logistic regression models (one per subject) and therefore standardize beta weights. I would use t-scores and then test t-scores from different models against zero to estimate whether there is an significant effect across subjects. However, I recently saw one line of code where betas are standardized by (??) beta=beta./sqrt(sum(beta^2)). Can anyone explain to me why you would standardize that way and what are the advantages compared to t-scores?