stepwise selection

Why is Stepwise Selection Important in Epidemiology?

In epidemiology, researchers often deal with large datasets containing numerous potential risk factors and confounders. Stepwise selection aids in simplifying the model by retaining only the most relevant variables. This is crucial for developing accurate and reliable models for disease prediction, risk assessment, and public health interventions.

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