When the logistic function is substituted for the normal, Thurstone's Case V specialization of the law of comparative judgment for paired comparison responses gives an identical equation for the estimation of item scale values, as does the Rasch formulation for direct responses. Comparisons are made. (Author/CTM)

Following a brief discussion of test construction by linear programing, the results of a study by F. B. Baker and others (1988) with respect to a uniform target is replicated. It is demonstrated that the result depends on characteristics of the item pool. (SLD)

The capability of the DIMTEST statistical test in assessing essential unidimensionality of item responses to real tests was investigated for 22 real tests of at least 25 items and 700 or more examinees. DIMTEST results on real tests were able to discriminate between essentially unidimensional and multidimensional tests. (SLD)

Item response theory-based appropriateness fit indices were used to identify and remove from a validation sample (n=201) those examinees whose response patterns did not match their trait levels. Although a person-fit index had little effect on validities, a multitest index was more promising. (SLD)

A method of automatically selecting items for inclusion in a test with constraints on item content and statistical properties was applied to real data. Tests constructed manually from the same data and constraints were compared to tests constructed automatically. Results show areas in which automated assembly can improve test construction. (SLD)

A least-squares solution for the method of paired comparisons is given. The approach provokes a theorem regarding the amount of data necessary and sufficient for a solution to be obtained. A measure of the internal consistency of the least-squares fit is developed. (Author/CTM)

Two methods are proposed for the construction of weakly parallel tests based on a prespecified information function. A method is then described for selecting weakly parallel tests that are optimal with respect to the Maximin criterion. Numerical examples demonstrate the practicality of the tests. (SLD)

Polynomial algorithms are presented that are used to solve selected problems in test theory, and computational results from sample problems with several hundred decision variables are provided that demonstrate the benefits of these algorithms. The algorithms are based on optimization theory in networks (graphs). (SLD)

Performance of the logistic regression (LR) procedure was compared to that of the Mantel Haenszel (MH) procedure in the detection of uniform and nonuniform differential item functioning on a simulation examining distributional properties of the LR and MH test statistics and the relative power of the two procedures. (SLD)

A model for solving very large item selection problems is presented. The model builds on binary programming applied to test construction. A heuristic for selecting items that satisfy the constraints in the model is also presented, and various problems are solved using the model and heuristic. (SLD)

This special issues describes multidimensional scaling (MDS), with emphasis on proximity and preference models. An introduction and six papers review statistical developments in MDS study design and scrutinize MDS research in four areas of application (consumer, social, cognitive, and vocational psychology). (SLD)

Previous person-fit research is extended through explication of an unexplored model for generating aberrant response patterns. The proposed model is then implemented to investigate the influence of test properties on the aberrancy detection power of a person-fit statistic. Difficulties of aberrancy detection are discussed. (SLD)

A theoretical framework for mastery testing based on item response theory and Bayesian decision theory is described and illustrated. Implementation depends on the availability of (1) a computerized test delivery system; (2) a pool of pretested items; and (3) a model relating observed test performance to true mastery status. (SLD)

This article proposes an item response theory (IRT) approach to constructing and scoring multidimensional pairwise preference items. Individual statements are administered and calibrated using a unidimensional single-stimulus model. Tests are created by combining multidimensional items with a small number of unidimensional pairings needed to…

Derivations of several item selection algorithms for use in fitting test items to target information functions (IFs) are described. These algorithms, which use an average growth approximation of target IFs, were tested by generating six test forms and were found to provide reliable fit. (SLD)