7.2 Relative Model-Data Fit at Test Level (Cont’d)

An information criterion is a measure gauging the quality of a statistical model by balancing the model complexity against how well the model fits the data.

It is based on $-2\log L(\mathbf{Y})$, but also takes the number of model parameters into account, which means it considers

• how well the model fits the data
• the complexity of the model

Information criteria are used to compare several competing models fitted to the same data set. All else being equal, a model with a lower information criterion is superior to a model with a higher value.