A latent trait model is described that is appropriate for use with tests that measure more than one dimension, and its application to both real and simulated test data is demonstrated. Procedures for estimating the parameters of the model are presented. The research objectives are to determine whether the two-parameter logistic model more adequately explains multidimensional test data than does the unidimensional version of the model, and to determine whether the results yielded by the application of the model are consistent with the results of another, more established multivariate data reduction procedure, factor analysis. The results of the analyses of the simulation data indicated that the parameters of the multidimensional model could be accurately estimated. The results of the goodness of fit analyses indicated that the multidimensional model could more adequately model simulated multidimensional response data than could the unidimensional model. The results of the analyses of the real data indicated that the multidimensional model also more adequately modeled multidimensional real data than did the unidimensional model. It was concluded that the use of a multidimensional model does seem to be feasible, and that more research is warranted. (Author/PN)