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.