Real test data of unknown structure were analyzed using both a unidimensional and a multidimensional latent trait model in an attempt to determine the underlying components of the test. The models used were the three-parameter logistic model and a multidimensional extension of the two-parameter logistic model. The basic design for the analysis of the data was to start with the unidimensional model, evaluate the fit of the model to the data, then increase the dimensionality of the model and perform the same analyses. The dimensionality of the model was to be increased until deviations from fit were acceptably small. Once acceptable fit was obtained, the item parameter estimates were to be analyzed to determine the structure of the ability components required by the test. The results of the analyses indicated that a two-dimensional solution yielded no better fit than a unidimensional solution, although the test data were selected to be multidimensional. From the results of the analyses it was concluded that the data had a difficulty factor that was sufficiently great as to dominate the other, intended factors. (Author)