An essential feature of the linear logistic test model (LLTM) is that item difficulties are explained using item design properties. By taking advantage of this explanatory aspect of the LLTM, in a mixture extension of the LLTM, the meaning of latent classes is specified by how item properties affect item difficulties within each class. To improve…

Modeling multidimensional test data with a unidimensional model can result in serious statistical errors, such as bias in item parameter estimates. Many methods exist for assessing the dimensionality of a test. The current study focused on DIMTEST. Using simulated data, the effects of sample size splitting for use with the ATFIND procedure for…

Cliff's Index "c" derived from an item dominance matrix is utilized in a clustering approach, termed extracting Reliable Guttman Orders (ERGO), to isolate Guttman-type item hierarchies. A comparison of factor analysis to the ERGO is made on social distance data involving multiple ethnic groups. (Author/BW)