Generalized Additive Models (GAMs) are a flexible class of models used in epidemiology to analyze complex relationships between predictors and outcomes. They extend the traditional Generalized Linear Models (GLMs) by allowing non-linear functions of the predictors while maintaining the interpretability of linear models. This is particularly useful in epidemiology, where relationships between variables can be intricate.
