Confirmatory factor analysis is presented as providing appropriate techniques for the analysis and evaluation of questionnaires and tests if the content of the measure can be identified as consisting of groups of items, with each group measuring only a single trait. This approach is contrasted with latent trait theory which assumes (and does not test) the assumption of unidimensionality. The first step in the analysis is the partitioning of the items into distinct scales or clusters, preferably on the basis of an a priori analysis of item content, although blind exploratory statistical methods may be substituted. The parameters of the model are estimated by oblique multiple groups factor analysis and include the correlations between items and factors, the correlations between the factors, and the communality of each item. This analysis will confirm, or disconfirm, the measurement model specified by the user. Chi square tests are provided for unidimensionality of clusters and parallelism. Appendices contain proofs and computer programs. (Author/CTM)