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Clemens Draxler; Andreas Kurz; Can Gürer; Jan Philipp Nolte – Journal of Educational and Behavioral Statistics, 2024
A modified and improved inductive inferential approach to evaluate item discriminations in a conditional maximum likelihood and Rasch modeling framework is suggested. The new approach involves the derivation of four hypothesis tests. It implies a linear restriction of the assumed set of probability distributions in the classical approach that…
Descriptors: Inferences, Test Items, Item Analysis, Maximum Likelihood Statistics
Finch, Holmes; Edwards, Julianne M. – Educational and Psychological Measurement, 2016
Standard approaches for estimating item response theory (IRT) model parameters generally work under the assumption that the latent trait being measured by a set of items follows the normal distribution. Estimation of IRT parameters in the presence of nonnormal latent traits has been shown to generate biased person and item parameter estimates. A…
Descriptors: Item Response Theory, Computation, Nonparametric Statistics, Bayesian Statistics
MacDonald, George T. – ProQuest LLC, 2014
A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…
Descriptors: Simulation, Item Response Theory, Models, Test Items
Seo, Dong Gi; Weiss, David J. – Educational and Psychological Measurement, 2013
The usefulness of the l[subscript z] person-fit index was investigated with achievement test data from 20 exams given to more than 3,200 college students. Results for three methods of estimating ? showed that the distributions of l[subscript z] were not consistent with its theoretical distribution, resulting in general overfit to the item response…
Descriptors: Achievement Tests, College Students, Goodness of Fit, Item Response Theory
Peer reviewedLin, Miao-Hsiang; Hsiung, Chao A. – Psychometrika, 1994
Two simple empirical approximate Bayes estimators are introduced for estimating domain scores under binomial and hypergeometric distributions respectively. Criteria are established regarding use of these functions over maximum likelihood estimation counterparts. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computation, Equations (Mathematics)
Peer reviewedSeong, Tae-Je – Applied Psychological Measurement, 1990
The sensitivity of marginal maximum likelihood estimation of item and ability (theta) parameters was examined when prior ability distributions were not matched to underlying ability distributions. Thirty sets of 45-item test data were generated. Conditions affecting the accuracy of estimation are discussed. (SLD)
Descriptors: Ability, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)
Peer reviewedMislevy, Robert J. – Psychometrika, 1984
Assuming vectors of item responses depend on ability through a fully specified item response model, this paper presents maximum likelihood equations for estimating the population parameters without estimating an ability parameter for each subject. Asymptotic standard errors, tests of fit, computing approximations, and details of four special cases…
Descriptors: Bayesian Statistics, Estimation (Mathematics), Goodness of Fit, Latent Trait Theory
Peer reviewedCohen, Allan S.; And Others – Journal of Educational Measurement, 1991
Detecting differential item functioning (DIF) on test items constructed to favor 1 group over another was investigated on parameter estimates from 2 item response theory-based computer programs--BILOG and LOGIST--using data for 1,000 White and 1,000 Black college students. Use of prior distributions and marginal-maximum a posteriori estimation is…
Descriptors: Black Students, College Students, Computer Assisted Testing, Equations (Mathematics)

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