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Babcock, Ben – Applied Psychological Measurement, 2011
Relatively little research has been conducted with the noncompensatory class of multidimensional item response theory (MIRT) models. A Monte Carlo simulation study was conducted exploring the estimation of a two-parameter noncompensatory item response theory (IRT) model. The estimation method used was a Metropolis-Hastings within Gibbs algorithm…
Descriptors: Item Response Theory, Sampling, Computation, Statistical Analysis
Classification Consistency and Accuracy for Complex Assessments under the Compound Multinomial Model
Lee, Won-Chan; Brennan, Robert L.; Wan, Lei – Applied Psychological Measurement, 2009
For a test that consists of dichotomously scored items, several approaches have been reported in the literature for estimating classification consistency and accuracy indices based on a single administration of a test. Classification consistency and accuracy have not been studied much, however, for "complex" assessments--for example,…
Descriptors: Classification, Reliability, Test Items, Scoring
Waller, Niels G. – Applied Psychological Measurement, 2008
Reliability is a property of test scores from individuals who have been sampled from a well-defined population. Reliability indices, such as coefficient and related formulas for internal consistency reliability (KR-20, Hoyt's reliability), yield lower bound reliability estimates when (a) subjects have been sampled from a single population and when…
Descriptors: Test Items, Reliability, Scores, Psychometrics

van der Linden, Wim J. – Applied Psychological Measurement, 1979
The restrictions on item difficulties that must be met when binomial models are applied to domain-referenced testing are examined. Both a deterministic and a stochastic conception of item responses are discussed with respect to difficulty and Guttman-type items. (Author/BH)
Descriptors: Difficulty Level, Item Sampling, Latent Trait Theory, Mathematical Models
Van Onna, Marieke J. H. – Applied Psychological Measurement, 2004
Coefficient "H" is used as an index of scalability in nonparametric item response theory (NIRT). It indicates the degree to which a set of items rank orders examinees. Theoretical sampling distributions, however, have only been derived asymptotically and only under restrictive conditions. Bootstrap methods offer an alternative possibility to…
Descriptors: Sampling, Item Response Theory, Scaling, Comparative Analysis

Nevo, Baruch – Applied Psychological Measurement, 1980
Computer simulations were employed to investigate sample sizes needed for item analysis when one's primary purpose is to rank order items in terms of indices of quality or to compare indices of quality against a fixed criterion. Necessary sample sizes were much smaller than those indicated by the literature. (Author/JKS)
Descriptors: Foreign Countries, Higher Education, Item Analysis, Sampling

Baker, Frank B. – Applied Psychological Measurement, 1996
Using the characteristic curve method for dichotomously scored test items, the sampling distributions of equating coefficients were examined. Simulations indicate that for the equating conditions studied, the sampling distributions of the equating coefficients appear to have acceptable characteristics, suggesting confidence in the values obtained…
Descriptors: Equated Scores, Item Response Theory, Sampling, Statistical Distributions
Karabatsos, George; Sheu, Ching-Fan – Applied Psychological Measurement, 2004
This study introduces an order-constrained Bayes inference framework useful for analyzing data containing dichotomous scored item responses, under the assumptions of either the monotone homogeneity model or the double monotonicity model of nonparametric item response theory (NIRT). The framework involves the implementation of Gibbs sampling to…
Descriptors: Inferences, Nonparametric Statistics, Item Response Theory, Data Analysis

Hanson, Bradley A.; And Others – Applied Psychological Measurement, 1993
The delta method was used to derive standard errors (SES) of the Levine observed score and Levine true score linear test equating methods using data from two test forms. SES derived without the normality assumption and bootstrap SES were very close. The situation with skewed score distributions is also discussed. (SLD)
Descriptors: Equated Scores, Equations (Mathematics), Error of Measurement, Sampling
Huitzing, Hiddo A. – Applied Psychological Measurement, 2004
This article shows how set covering with item sampling (SCIS) methods can be used in the analysis and preanalysis of linear programming models for test assembly (LPTA). LPTA models can construct tests, fulfilling a set of constraints set by the test assembler. Sometimes, no solution to the LPTA model exists. The model is then said to be…
Descriptors: Mathematical Applications, Simulation, Item Sampling, Item Response Theory

Wilcox, Rand R. – Applied Psychological Measurement, 1980
This paper discusses how certain recent technical advances might be extended to examine proficiency tests which are conceptualized as representing a variety of skills with one or more items per skill. In contrast to previous analyses, errors in the item level are included. (Author/BW)
Descriptors: Mastery Tests, Minimum Competencies, Minimum Competency Testing, Sampling

Meijer, Rob R.; And Others – Applied Psychological Measurement, 1995
Three methods based on the nonparametric item response theory (IRT) of R. J. Mokken for the estimation of the reliability of single dichotomous test items are discussed. Analytical and Monte Carlo studies show that one method, designated "MS," is superior because of smaller bias and smaller sampling variance. (SLD)
Descriptors: Estimation (Mathematics), Item Response Theory, Monte Carlo Methods, Nonparametric Statistics