The choice of method depends on various factors, including the nature of the data, the research question, and the complexity of the relationship. Here are a few considerations:
Data Structure: If the data has a hierarchical structure, mixed-effects models may be more appropriate. Model Interpretability: If interpretability is crucial, simpler methods like polynomial regression or splines may be preferable. Flexibility vs. Overfitting: More flexible methods like GAMs can capture complex relationships but may require careful management to avoid overfitting.
