Conjunctive item response models are introduced such that: (1) sufficient statistics for latent traits are not necessarily additive in item scores; (2) items are not necessarily locally independent; and (3) existing compensatory (additive) item response models including the binomial, Rasch, logistic, and general locally independent model are…

One of the important underlying assumptions of all item response theory (IRT) models is that of local independence. This assumption requires that the response to an item on a test not be influenced by the response to any other items. This assumption is often taken for granted, with little or no scrutiny of the response process required to answer…

To assess the effects of correlated abilities on test characteristics, and to explore the effects of correlated abilities on the use of a multidimensional item response theory model which does not explicitly account for such a correlation, two tests were constructed. One had two relatively unidimensional subsets of items, the other had all…

Critics have occasionally asserted that the number of factors in the 16PF tests is too large. This study discusses factor-analytic methodology and reviews more than 50 studies in the field. It concludes that the number of important primaries encapsulated in the series is no fewer than the stated number. (Author/JAZ)

Multidimensional item response data were created. The strength of a general factor, the number of common factors, the distribution of items loadingon common factors, and the number of items in simulated tests were manipulated. LOGIST effectively recovered both item and trait parameters in nearly all of the experimental conditions. (Author/JAZ)

This paper deals with test fairness regarding a test consisting of two parts: (1) a "common" section, taken by all students; and (2) a "variable" section, in which some students may answer a different set of questions from other students. For example, a test taken by several thousand students each year contains a common multiple-choice portion and…

Although perfectly scalable items rarely occur in practice, Guttman's concept of a scale has proved to be valuable to the development of measurement theory. If the score distribution is uniform and there is an equal number of items at each difficulty level, both the elements and the eigenvalues of the Pearson correlation matrix of dichotomous…

A previous study of pre-equating the Scholastic Aptitude Test (SAT) using item response theory provided unacceptable equating results for SAT-mathematical data. The purpose of this study was to investigate two possible explanations for these unacceptable pre-equating results. Specifically, the calibration process, which made use of the…

The purpose of this study was to investigate the effect of using multidimensional items in a computer adaptive test (CAT) setting which assumes a unidimensional item response theory (IRT) framework. Previous research has suggested that the composite of multidimensional abilities being estimated by a unidimensional IRT model is not constant…

Four discrimination indices were compared, using score distributions which were normal, bimodal, and negatively skewed. The score distributions were systematically varied to represent the common circumstances of a military training situation using criterion-referenced mastery tests. Three 20-item tests were administered to 110 simulated subjects.…

This report contains the Proceedings of the 1982 Item Response Theory and Computerized Adaptive Testing Conference. The papers and their discussions are organized into eight sessions: (1) "Developments in Latent Trait Theory," with papers by Fumiko Samejima and Michael V. Levine; (2) "Parameter Estimation," with papers by…

This report was designed to respond to two major methodological shortcomings in the item bias literature: (1) misfitting test models; and (2) the use of significance tests. Specifically, the goals of the research were to describe a newly developed method known as the "plot method" for identifying potentially biased test items and to…