The results of a series of simulation studies designed to investigate the influence of guessing and item pool characteristics on the bias, accuracy, and information properties of the trait estimates derived from Owen's Bayesian sequential testing strategy are reported. (RC)

Maximum likelihood and Bayesian procedures are presented for item selection and scoring of multidimensional adaptive tests. A demonstration with simulated response data illustrates that multidimensional adaptive testing can provide equal or higher reliabilities with fewer items than are required in one-dimensional adaptive testing. (SLD)

In this article, a new method is presented and implemented for deriving a scale of socioeconomic status (SES) from international survey data using a multilevel Bayesian item response theory (IRT) model. The proposed model incorporates both international anchor items and nation-specific items and is able to (a) produce student family SES scores…

Comments are made on the review papers presented by six Dutch psychometricians: Ivo Molenaar, Wim van der Linden, Ed Roskam, Arnold Van den Wollenberg, Gideon Mellenbergh, and Dato de Gruijter. Molenaar has embraced a pragmatic viewpoint on Bayesian methods, using both empirical and pure approaches to solve educational research problems. Molenaar…

The analytically derived asymptotic standard errors (SEs) of maximum likelihood (ML) item estimates can be approximated by a mathematical function without examinees' responses to test items, and the empirically determined SEs of marginal maximum likelihood estimation (MMLE)/Bayesian item estimates can be obtained when the same set of items is…

"Item models" (LaDuca, Staples, Templeton, & Holzman, 1986) are classes from which it is possible to generate/produce items that are equivalent/isomorphic to other items from the same model (e.g., Bejar, 1996; Bejar, 2002). They have the potential to produce large number of high-quality items at reduced cost. This paper introduces…

Monte Carlo simulation was used to investigate score bias and information characteristics of Owen's Bayesian adaptive testing strategy, and to examine possible causes of score bias. Factors investigated in three related studies included effects of item discrimination, effects of fixed vs. variable test length, and effects of an accurate prior…

Recent work in factor analysis of categorical variables is reviewed, emphasizing a generalized least squares solution and a maximum likelihood approach. A common factor model for dichotomous items is introduced, and the estimation of factor loadings from matrices of tetracorrelations is discussed. (LMO)

An empirical review of test items is described as an essential step in criterion-referenced test development. The concept of test items' instructional sensitivity is introduced, and research is briefly reviewed which describes four theoretical contexts in which instructional sensitivity indexes have been observed: criterion-referenced; classical…

This report examines how selection fairness is influenced by the characteristics of a selection instrument in terms of its distribution of item difficulties, level of item discrimination, degree of item bias, and testing strategy. Computer simulation was used in the administration of either a conventional or Bayesian adaptive ability test to a…

Assessing fit of psychometric models has always been an issue of enormous interest, but there exists no unanimously agreed upon item fit diagnostic for the models. Bayesian networks, frequently used in educational assessments (see, for example, Mislevy, Almond, Yan, & Steinberg, 2001) primarily for learning about students' knowledge and…

Instructional sensitivity indices are compared from four perspectives: (1) criterion-referenced testing; (2) classical test theory; (3) item response theory; and (4) Bayesian theory. Instructional sensitivity is defined as the tendency of a test item to vary in difficulty as a function of instruction. The instructional sensitivity of the items in…

A study was conducted to compare tailored testing procedures based on a Bayesian ability estimation technique and on a maximum likelihood ability estimation technique. The Bayesian tailored testing procedure selected items so as to minimize the posterior variance of the ability estimate distribution, while the maximum likelihood tailored testing…

A scaling procedure is proposed, based on item response theory (IRT), to fit non-hierarchical test structure as well. The binary scores of a test of English were used for calculating the probabilities of answering each item correctly. The probability matrix was factor analyzed, and the difficulty intervals or estimates corresponding to the factors…

The issue of test-item selection in support of decision making in adaptive testing is considered. The number of items needed to make a decision is compared for two approaches: selecting items from an item pool that are most informative at the decision point or selecting items that are most informative at the examinee's ability level. The first…