One of the major assumptions of latent trait theory is that the items in a test measure a single dimension. This report describes an investigation of procedures for forming a set of items that meet this assumption. Factor analysis, nonmetric multidimensional scaling, cluster analysis and latent trait analysis were applied to simulated and real test data to determine which technique could best form a unidimensional set of items. Theoretical and empirical evaluations were also made of the effects of guessing on the dimensionality of test data. The results indicated that guessing affected highly discriminating items more so than poorly discriminating items. Of the procedures evaluated for sorting items into unidimensional item sets, principal factor analysis of phi coefficients gave the best results overall. In summary, guessing does have an effect on test data, but the effect is not very large unless items of extreme difficulty are present in the test. Of the procedures evaluated, traditional factor analytic techniques gave the most useful information for sorting test items into homogeneous sets. (Author/GK)