Date of Original Version
Cross-validation is the process of comparing a model’s predictions to data that were not used in the estimation of model parameters. Cross-validation may have some value in identifying source models, especially in cases where the corresponding fitted models require the estimation of different numbers of parameters. Some of the information available from cross-validation is illustrated using a linear and a threshold model, and goodness-of-fit patterns are contrasted with those of conventional model-fitting.
Collyer, C. E. Behavior Research Methods, Instruments, & Computers (1986) 18: 618. https://doi.org/10.3758/BF03201437
Available at: https://doi.org/10.3758/BF03201437