How Does Resampling Improve Epidemiological Analyses?

Resampling methods offer several benefits in epidemiological research:

Non-parametric Nature: They do not rely on the assumption of normality, making them suitable for data that do not fit traditional parametric models.
Small Sample Sizes: They are particularly useful when dealing with small sample sizes, where traditional statistical methods may not be reliable.
Robustness: By generating multiple samples, resampling methods help assess the robustness and variability of the results, providing more reliable estimates.
Complex Models: They facilitate the evaluation of complex models and interactions, which might be difficult to analyze using traditional methods.