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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Debelak, Rudolf; Strobl, Carolin – Educational and Psychological Measurement, 2019
M-fluctuation tests are a recently proposed method for detecting differential item functioning in Rasch models. This article discusses a generalization of this method to two additional item response theory models: the two-parametric logistic model and the three-parametric logistic model with a common guessing parameter. The Type I error rate and…
Descriptors: Test Bias, Item Response Theory, Statistical Analysis, Maximum Likelihood Statistics
Mahmud, Jumailiyah; Sutikno, Muzayanah; Naga, Dali S. – Educational Research and Reviews, 2016
The aim of this study is to determine variance difference between maximum likelihood and expected A posteriori estimation methods viewed from number of test items of aptitude test. The variance presents an accuracy generated by both maximum likelihood and Bayes estimation methods. The test consists of three subtests, each with 40 multiple-choice…
Descriptors: Maximum Likelihood Statistics, Computation, Item Response Theory, Test Items
Lang, Kyle M.; Little, Todd D. – International Journal of Behavioral Development, 2014
We present a new paradigm that allows simplified testing of multiparameter hypotheses in the presence of incomplete data. The proposed technique is a straight-forward procedure that combines the benefits of two powerful data analytic tools: multiple imputation and nested-model ?2 difference testing. A Monte Carlo simulation study was conducted to…
Descriptors: Hypothesis Testing, Data Analysis, Error of Measurement, Computation
Doebler, Anna; Doebler, Philipp; Holling, Heinz – Psychometrika, 2013
The common way to calculate confidence intervals for item response theory models is to assume that the standardized maximum likelihood estimator for the person parameter [theta] is normally distributed. However, this approximation is often inadequate for short and medium test lengths. As a result, the coverage probabilities fall below the given…
Descriptors: Foreign Countries, Item Response Theory, Computation, Hypothesis Testing
Broatch, Jennifer; Lohr, Sharon – Journal of Educational and Behavioral Statistics, 2012
Measuring teacher effectiveness is challenging since no direct estimate exists; teacher effectiveness can be measured only indirectly through student responses. Traditional value-added assessment (VAA) models generally attempt to estimate the value that an individual teacher adds to students' knowledge as measured by scores on successive…
Descriptors: Teacher Effectiveness, Models, Maximum Likelihood Statistics, Computation
Gittler, Georg; Fischer, Gerhard – Journal of Educational and Behavioral Statistics, 2011
The article extends and applies previous approaches by Klauer and Fischer to the statistical evaluation of ability changes in tests conforming to the Rasch model (RM). Exact uniformly most powerful unbiased (UMPU) hypothesis tests and uniformly most accurate (UMA) confidence intervals (CIs) for the amount of change can be constructed for each…
Descriptors: Item Response Theory, Change, Spatial Ability, Classical Music
Raykov, Tenko; Marcoulides, George A. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
A latent variable modeling approach for examining population similarities and differences in observed variable relationship and mean indexes in incomplete data sets is discussed. The method is based on the full information maximum likelihood procedure of model fitting and parameter estimation. The procedure can be employed to test group identities…
Descriptors: Models, Comparative Analysis, Groups, Maximum Likelihood Statistics

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