Effective model evaluation is not a single, simple procedure, but comprises several interrelated steps that cannot be separated from each other or from the purpose and process of model construction. We draw attention to several statistical and graphical procedures that may be used both with data used for model calibration and with data used in the evaluation of the model. We emphasize that the validity of conclusions depends on the validity of assumptions. These principles should be kept in mind throughout model construction and evaluation
