Internal Validation
“Internal validation assesses validity for the setting where the development data originated from”2. Internal validity is also called “reproducibility” which means the ability to produce accurate predictions among individuals not included in the development of the model but from the same population3. In internal validation, generally, the dataset is divided into two categories. One category is called the ”training” dataset, which is used to create the model, while the other category is called the ”test” or “validation” dataset, which is used to assess the model performance. Internal validation can be performed in different ways. We discuss here some of the major internal validation procedures.