Cross-validation of findings from a prediction study is particularly important for
A) determining the stability of the base rate across replication samples.
B) improving the selection ratio.
C) identifying nonlinear relationships among predictor variables.
D) checking for shrinkage when the original study is replicated.

Question

Quizplus · Accepted Answer

Cross-validation is crucial for checking for shrinkage in predictive accuracy when a study is replicated. Shrinkage occurs when a model performs exceptionally well on the sample data it was developed on but less well on new, unseen data. Cross-validation helps in assessing the model's generalizability and stability across different samples.

Cross-Validation of Findings from a Prediction Study Is Particularly Important