The validation of mathematical models constructed for the dynamic analysis of critical structures is a very important, but complex, process. The essential requirement is to provide confirmation, using independent and more reliable data than that presented by the model in question, that the subject model is capable of describing the essential physics of the structure's behaviour within the required accuracy. In this paper, the procedures of model validation using experimental data on a structure are summarised and applied to a structural dynamics validation problem developed by Sandia National Laboratories. One of the essential issues is to separate out any non-linear features of the system and to construct an appropriate linear model that is as accurate as possible to cope with variability of the subsystem structures. The linear model, which is constructed using simulated test data from an assembly of sample subsystems, is expressed as a mean model with a standard deviation. It is further used in the system response prediction for system accreditation and target application under specified excitation loads. The influence of the weak non-linearity features are neglected in the system response prediction because the experimental method used to derive the test data obscured the non-linear effects and precluded their identification. Further consideration of identification and modelling of the non-linear element for the Sandia 3DOF calibration system is discussed to evaluate its influence on the accuracy of the spatial model.