Why is Adjusted R Squared Important in Epidemiology?
In epidemiology, researchers often deal with complex datasets containing multiple variables. When building regression models to study associations between risk factors and health outcomes, it's essential to account for the number of predictors to avoid overfitting. Overfitting occurs when a model describes random error or noise instead of the underlying relationship, leading to poor generalizability to new data. Adjusted R squared helps mitigate this risk by providing a more accurate measure of model performance.
