The algorithm developed by B. A. Schneider (1980) for analysis of paired comparisons of psychological intervals is replaced by one proposed by R. M. Johnson. Monte Carlo simulations of pairwise dissimilarities and pairwise conjoint effects show that Johnson's algorithm can provide good metric recovery. (SLD)

The difference between compensatory and non-compensatory item response theory (IRT) models in terms of the dimensionality of test data generated by them, and its effect on the model-data-fit were examined. The STRESS (proportion of variance not accounted for by the multidimensional scaling model) and RSQ (proportion of variance accounted for by…

Many multidimensional item response theory (IRT) models have been proposed. A comparison is made between the so-called full information models and the models that use only pairwise information. Three multidimensional models described are: (1) the compensatory model of R. D. Bock and M. Aitken (1981) using the computer program TESTFACT; (2) a model…

Two sets of real sorting data from 50 college students are used to compare results of multidimensional scaling of raw co-occurrence frequencies or dissimilarity measures (D) and profile distances (delta) to determine which yields a better representation of the underlying structure of 2 sets of stimuli. Slight differences are discussed. (SLD)

The following seven statistical procedures are compared in terms of the ability to recover a unidimensional latent trait from Likert-type data: (1) factor analysis based on Pearson correlations (FA-PR); (2) factor analysis based on polychoric correlations (FA-PL); (3) the graded response model in item response theory (IRT-GRM); (4) internal…

Equatings were performed on both simulated and real data sets using common-examinee design and two abilities for each examinee. Results indicate that effective equating, as measured by comparability of true scores, is possible with the techniques used in this study. However, the stability of the ability estimates proved unsatisfactory. (TJH)

The ability of 3-way INDSCAL and ALSCAL models to recover true structure in proximity data based on 2-dimensional configurations varying in number of subjects (15 and 20) and stimuli, amount of error, and monotonic transformation is examined. INDSCAL outperformed metric and nonmetric ALSCAL in all conditions. (SLD)