How is Cross Validation Implemented in Epidemiological Studies?

To implement cross validation in epidemiological studies, researchers typically follow these steps:

Data Preparation: Clean and preprocess the data, handling missing values and normalizing features as necessary.
Partitioning the Data: Split the dataset into training and testing subsets according to the chosen cross validation method.
Model Training: Train the model on the training subsets.
Model Testing: Test the model on the testing subsets and record the performance metrics.
Performance Evaluation: Aggregate the performance metrics across all folds to get an overall assessment of the model's predictive ability.