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.
