I am planning to conduct a path analysis to figure out the effect from X to Y. (not causality)
I personally believe that most statistical models should not be overfitted. Whether developing a predictive or explanatory model, overfitting should be avoided. Otherwise, the estimated parameters are not trustworthy.
However, some research paper or my laboratory member do not pay attention to this. He says that he does not consider overfitting when he fits a linear model for interpretation.
Is my idea wrong? I hope someone gives me a comment or resource for these.