Generalized Additive Models

Generalized Additive Models (GAMs) are a type of statistical approach used to understand complex data relationships. They allow researchers to create flexible models by combining multiple predictors (like age, income, or education) in a way that each can influence the outcome separately. Instead of fitting a single straight line, GAMs can use curved lines for each predictor, helping to capture more intricate patterns in the data. This makes GAMs particularly useful in fields like medicine, economics, and environmental science, where relationships can be nonlinear and varied across different situations.