A statistical method is described and illustrated which provides confidence envelopes around item response functions. Examples of 95 percent confidence envelopes for the one-, two-, and three-parameter logistic response models are given. In addition, the authors describe N-line plots, which show the genesis of the envelope as well as the density…

The applicability of a new multiple-group factor analysis of dichotomous variables is shown and contrasted with the item response theory approach to item bias analysis. Situations are considered where the same set of test items has been administered to more than one group of examinees. (Author/BS).

The methods and approaches for estimating the operating characteristics of the discrete item responses without assuming any mathematical form have been developed and expanded. It has been made possible that, even if the test information function of a given test is not constant for the interval of ability of interest, it is used as the Old Test.…

Drawing on recently developed methodology for structural equation modeling with categorical data, this article proposes a new approach for investigating the behavior of dichotomously scored test items in relation to other relevant (observed) variables. A linear structural model relates the latent ability variable to a set of observed scores.…

For many reasons, students do not always perform on tests in ways that are congruent with their true abilities or achievement levels. Problems of this sort may be especially common on Title I evaluations where the tests administered are too difficult for a large percentage of the students. Such considerations raise the questions of whether…

There is a unity underlying the diversity of models for the analysis of multivariate data. Essentially, they constitute a family of models, most generally nonlinear, for structural/functional relations between variables drawn from a behavior domain. (Author)

This paper provides an up-to-date review of the relationship between item response theory (IRT) and (nonlinear) common factor theory and draws out of this relationship some implications for current and future research in IRT. Nonlinear common factor analysis yields a natural embodiment of the weak principle of local independence in appropriate…

This paper reviews the application of the EM Algorithm to marginal maximum likelihood estimation of parameters in the latent class model and extends the algorithm to the case where there are monotone homogeneity constraints on the item parameters. It is shown that the EM algorithm can be used to obtain marginal maximum likelihood estimates of the…

A logistic model was used to generate data to serve as a proxy for an immediate retest from item responses to a fourth grade standardized reading comprehension test of 45 items. Assuming that the actual test may be considered a pretest and the proxy data may be considered a retest, the effect of regression was investigated using a percentage of…

Standard procedures for estimating item parameters in Item Response Theory models make no use of auxiliary information about test items, such as their format or content, or the skills they require for solution. This paper describes a framework for exploiting this information, thereby enhancing the precision and stability of item parameter…

A necessary prerequisite to the operational use of item response theory (IRT) in any testing program is the investigation of the feasibility of such an approach. This report presents the results of such research for the Graduate Management Admission Test (GMAT). Despite the fact that GMAT data appear to violate a basic assumption of the…