Suppose my goal is to understand the relationship between variable $y$ and covariates $X$. Let's say $y$ is a rate, the number of success in $n$ trials, therefore bounded between $0$ and $1$.
Now I have (at least) 2 approaches. Take the log of $y$ and use a linear model, or use logistic regression. Logistic regression is the more theoretically appropriate model but estimation can lead to problems (example) that the linear method doesn't have.
How do I choose between them when the goal is understanding, not predicting? I thought of using AIC or a similar criterion but the target is not the same so I don't think that will work.