I am data science beginner, and I have a question about methods that I could use to analyze the following data. It is a simple case, I am trying to check the influence of cohabitation before marriage and being a believer on divorce. So, I am asking what model could I build to test it? The only thing I did for now was checking the conditional probability of those cathegories. I know that the data is very simple, but I read about so many various tehcniques that I feel paralyzed and I don't really know what should be the best option. I am open for classical statistical methods, bayesian methods, and building ML models.
I think that chi square test would be suitable, but I am also interested in more sophisticated methods.
(This matrix is just a visualization, I have these data in df with IDs and stuff. Source of the data is NSFG)(I am using R)