Various attempts at solving the oscillation source location problem have been detailed in the literature and each has had their own shortcomings. The dynamic behaviour of a power system is such that periods of instability may arise that are not solely due to large generators sitting beside each other in large plants. While these large machines operating at near full capacity certainly have an effect on modes in the system, the trigger may be something more inconspicuous like a smaller generator or load, or group thereof, that can produce instability in a number of system modes. The use of real-time continuous dynamics monitoring often indicates dynamic behaviour that was not anticipated by the model-based studies. In such cases it can be difficult to track down the sources of problems using conventional tools. This paper details the possibility of diagnosing the causes of problems related to oscillatory stability using measurement-based techniques, with measurements derived from dynamic power system models. A dynamic model based on a real system is used to simulate periods of instability, so that the methodology can be applied to the data to determine the interaction of significant variables that contribute to poor mode damping. To this end, the discrete wavelet transform is used in conjunction with general linear models and logic regression to fit the model data and to predict the system response with minimum statistical deviance. This measurement-based modelling technique could then be used in real time with real system variables to determine the best course of action to rectify a range of dynamics problems.