In epidemiology, researchers often deal with complex, nonlinear relationships between exposure variables and health outcomes. Natural splines allow for these relationships to be modeled without assuming a predefined form. This flexibility is crucial in identifying associations that could be missed with more rigid models. Additionally, their boundary constraints reduce the risk of overfitting, enhancing the robustness of the findings.
