Stepwise selection is a statistical method used in epidemiology for model selection. It is an iterative process that involves adding or removing predictors based on specific criteria, such as the p-value, Akaike Information Criterion (AIC), or Bayesian Information Criterion (BIC). This method helps in identifying the most significant variables that contribute to the outcome of interest, improving the model's predictive power and interpretability.
