A review of model-selection criteria is presented, suggesting their similarities. Some problems treated by hypothesis tests may be more expeditiously treated by the application of model-selection criteria. Multivariate analysis, cluster analysis, and factor analysis are considered. (Author/GDC)

An approximate relationship is devised between the unidimensional model used in data analysis and a multidimensional model hypothesized to be generating the item responses. Scale shrinkage is successfully predicted for several sets of simulated data. (Author/LMO)

A Bradley-Terry type model for paired comparisons is considered which allows for individual parameters and corresponding parameters for the choice-alternatives. Model is applied to data from a Danish investigation of blue collar attitudes towards alternative social gains. Model is compared to one suggested by Schonemann and Wang. (RC)

Special cases of the factor analysis model are developed for four selection situations. Methods are suggested whereby parameters in each case can be estimated using a maximum likelihood procedure recently developed by Joreskog. (Author)

Considers the study of similarities and differences in factor structures between different groups. (AG)

The oblimax, promax, maxplane, and Harris-Kaiser techniques are compared. (Author)

Statistical properties of person fit indices are reviewed as indicators of the extent to which a person's score pattern is in agreement with a measurement model. Distribution of a fit index and ability-free fit evaluation are discussed. The null distribution was simulated for a test of 20 items. (SLD)

Multivariate distributions are studied in which all bivariate regressions can be linearized by separate transformation of each of the variables. A two-stage procedure, first scaling the variables optimally and then fitting a simultaneous equations model, is studied in detail. (SLD)

The statistical analysis of processing tree models is advanced by showing how the parameters of estimation and hypothesis testing, based on the likelihood functions, can be accomplished by adapting the expectation-maximization (EM) algorithm. The adaptation makes it easy to program a personal computer to accomplish the stages of statistical…

In the present paper, a new family of item response theory (IRT) models for dichotomous item scores is proposed. Two basic assumptions define the most general model of this family. The first assumption is local independence of the item scores given a unidimensional latent trait. The second assumption is that the odds-ratios for all item-pairs are…