Hello everyone,

I am planning to design a model that can predict individuals with high or low psychosis-proneness by looking at the brain connectivity measures in 114 regions, age, gender, IQ, SES, polygenic risk score for psychosis (PRS), and environmental risk score for psychosis (ERS). In this way, I am planning to investigate the brain regions that serve to distinguish high and low psychosis-proneness by using machine learning. However, my sample includes healthy twin and sibling data; hence, my data is not independent. I could group the sample into high and low psychosis-proneness based on weighted positive symptom severity.

Therefore, I would like to ask whether there are any codes or approaches that you can share with me.

My data looks like the image I shared (I did not add the PRS since I do not have the information yet).

Thank you for your help!