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Feinberg, Richard A.; von Davier, Matthias – Journal of Educational and Behavioral Statistics, 2020
The literature showing that subscores fail to add value is vast; yet despite their typical redundancy and the frequent presence of substantial statistical errors, many stakeholders remain convinced of their necessity. This article describes a method for identifying and reporting unexpectedly high or low subscores by comparing each examinee's…
Descriptors: Scores, Probability, Statistical Distributions, Ability
Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2015
The maximum likelihood estimate (MLE) of the ability parameter of an item response theory model with known item parameters was proved to be asymptotically normally distributed under a set of regularity conditions for tests involving dichotomous items and a unidimensional ability parameter (Klauer, 1990; Lord, 1983). This article first considers…
Descriptors: Item Response Theory, Maximum Likelihood Statistics, Test Items, Ability
Pokropek, Artur – Journal of Educational and Behavioral Statistics, 2016
A response model that is able to detect guessing behaviors and produce unbiased estimates in low-stake conditions using timing information is proposed. The model is a special case of the grade of membership model in which responses are modeled as partial members of a class that is affected by motivation and a class that responds only according to…
Descriptors: Reaction Time, Models, Guessing (Tests), Computation
Tao, Jian; Shi, Ning-Zhong; Chang, Hua-Hua – Journal of Educational and Behavioral Statistics, 2012
For mixed-type tests composed of both dichotomous and polytomous items, polytomous items often yield more information than dichotomous ones. To reflect the difference between the two types of items, polytomous items are usually pre-assigned with larger weights. We propose an item-weighted likelihood method to better assess examinees' ability…
Descriptors: Test Items, Weighted Scores, Maximum Likelihood Statistics, Statistical Bias
Magis, David; Raiche, Gilles; Beland, Sebastien – Journal of Educational and Behavioral Statistics, 2012
This paper focuses on two likelihood-based indices of person fit, the index "l[subscript z]" and the Snijders's modified index "l[subscript z]*". The first one is commonly used in practical assessment of person fit, although its asymptotic standard normal distribution is not valid when true abilities are replaced by sample…
Descriptors: Goodness of Fit, Item Response Theory, Computation, Ability
Schuster, Christof; Yuan, Ke-Hai – Journal of Educational and Behavioral Statistics, 2011
Because of response disturbances such as guessing, cheating, or carelessness, item response models often can only approximate the "true" individual response probabilities. As a consequence, maximum-likelihood estimates of ability will be biased. Typically, the nature and extent to which response disturbances are present is unknown, and, therefore,…
Descriptors: Computation, Item Response Theory, Probability, Maximum Likelihood Statistics
Harring, Jeffrey R. – Journal of Educational and Behavioral Statistics, 2009
The nonlinear mixed effects model for continuous repeated measures data has become an increasingly popular and versatile tool for investigating nonlinear longitudinal change in observed variables. In practice, for each individual subject, multiple measurements are obtained on a single response variable over time or condition. This structure can be…
Descriptors: Regression (Statistics), Computation, Measurement, Models

Rossi, Natasha; Wang, Xiaohui; Ramsay, James O. – Journal of Educational and Behavioral Statistics, 2002
Combined several developments in statistics and item response theory to develop a procedure for analysis of dichotomously scored test data. This version of nonparametric item response analysis, as illustrated through simulation and with data from other studies, marginalizes the role of the ability parameter theta. (SLD)
Descriptors: Ability, Item Response Theory, Nonparametric Statistics, Scores

Bradlow, Eric T. – Journal of Educational and Behavioral Statistics, 1996
The three-parameter logistic (3-PL) model is described and a derivation of the 3-PL observed information function is presented for a single binary response from one examinee with known item parameters. Formulas are presented for the probability of negative information and for the expected information (always nonnegative). (SLD)
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Item Response Theory

Veerkamp, Wim J. J. – Journal of Educational and Behavioral Statistics, 2000
Showed how Taylor approximation can be used to generate a linear approximation to a logistic item characteristic curve and a linear ability estimator. Demonstrated how, for a specific simulation, this could result in the special case of a Robbins-Monro item selection procedure for adaptive testing. (SLD)
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Selection

Duijn, Marijtje A. J. van; Jansen, Margo G. H. – Journal of Educational and Behavioral Statistics, 1995
The Rasch Poisson Counts Model, a unidimensional latent trait model for tests that postulates that intensity parameters are products of test difficulty and subject ability parameters, is expanded into the Dirichlet-Gamma-Poisson model that takes into account variation between subjects and interaction between subjects and tests. (SLD)
Descriptors: Ability, Achievement Tests, Difficulty Level, Estimation (Mathematics)

Douglas, Jeffrey A.; And Others – Journal of Educational and Behavioral Statistics, 1996
A procedure for detection of differential item functioning (DIF) is proposed that amalgamates SIBTEST and kernel-smoothed item response function estimation to assess DIF as a function of the latent trait theta that the test is designed to measure. Smoothed SIBTEST is studied through simulation and real data analysis. (SLD)
Descriptors: Ability, Equations (Mathematics), Estimation (Mathematics), Item Bias

van der Linden, Wim J. – Journal of Educational and Behavioral Statistics, 1999
Proposes an algorithm that minimizes the asymptotic variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The criterion results in a closed-form expression that is easy to evaluate. Also shows how the algorithm can be modified if the interest is in a test with a "simple ability structure."…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing

Spray, Judith A.; Reckase, Mark D. – Journal of Educational and Behavioral Statistics, 1996
Two procedures for classifying examinees into categories, one based on the sequential probability ratio test (SPRT) and the other on sequential Bayes methodology, were compared to determine which required fewer items for classification. Results showed that the SPRT procedure requires fewer items to achieve the same accuracy level. (SLD)
Descriptors: Ability, Bayesian Statistics, Classification, Comparative Analysis

Berger, Martijn P. F.; Veerkamp, Wim J. J. – Journal of Educational and Behavioral Statistics, 1997
Some alternative criteria for item selection in adaptive testing are proposed that take into account uncertainty in the ability estimates. A simulation study shows that the likelihood weighted information criterion is a good alternative to the maximum information criterion. Another good alternative uses a Bayesian expected a posteriori estimator.…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing