Epidemiologists use k-fold cross validation for several reasons: 1. Improved Accuracy: By averaging the results over k trials, we reduce the variability and obtain a more accurate estimate of the model’s performance. 2. Generalizability: It helps to ensure that the model is not overfitting to a particular subset of the data, thus enhancing its ability to generalize to new datasets. 3. Efficient Use of Data: Especially important in epidemiology where data may be scarce or expensive to collect. K-fold cross validation makes efficient use of the available data.
