How to compute and report subscores for a test that was originally designed for reporting scores on a unidimensional scale has been a topic of interest in recent years. In the research reported here, we describe an application of multidimensional item response theory to identify a subscore structure in a test designed for reporting results using a unidimensional scale. This research also dealt with the problem of planned missing data due to low levels of item overlap among multiple test forms. Furthermore, we provided evidence for the generalizability of the multidimensional structure using multiple forms of the same test. We also compared the subscores from multiple groups to show the usefulness of the subscores. The research provides evidence that subscores can be identified and produced to provide useful information about different constructs for multiple examinee groups even though the test data were well fit by a unidimensional model.