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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
Ma, Wenchao; de la Torre, Jimmy – Journal of Educational and Behavioral Statistics, 2019
Solving a constructed-response item usually requires successfully performing a sequence of tasks. Each task could involve different attributes, and those required attributes may be "condensed" in various ways to produce the responses. The sequential generalized deterministic input noisy "and" gate model is a general cognitive…
Descriptors: Test Items, Cognitive Measurement, Models, Hypothesis Testing
Ayodele, Alicia Nicole – ProQuest LLC, 2017
Within polytomous items, differential item functioning (DIF) can take on various forms due to the number of response categories. The lack of invariance at this level is referred to as differential step functioning (DSF). The most common DSF methods in the literature are the adjacent category log odds ratio (AC-LOR) estimator and cumulative…
Descriptors: Statistical Analysis, Test Bias, Test Items, Scores
Baghaei, Purya; Kubinger, Klaus D. – Practical Assessment, Research & Evaluation, 2015
The present paper gives a general introduction to the linear logistic test model (Fischer, 1973), an extension of the Rasch model with linear constraints on item parameters, along with eRm (an R package to estimate different types of Rasch models; Mair, Hatzinger, & Mair, 2014) functions to estimate the model and interpret its parameters. The…
Descriptors: Item Response Theory, Models, Test Validity, Hypothesis Testing
Raykov, Tenko; Marcoulides, George A.; Lee, Chun-Lung; Chang, Chi – Educational and Psychological Measurement, 2013
This note is concerned with a latent variable modeling approach for the study of differential item functioning in a multigroup setting. A multiple-testing procedure that can be used to evaluate group differences in response probabilities on individual items is discussed. The method is readily employed when the aim is also to locate possible…
Descriptors: Test Bias, Statistical Analysis, Models, Hypothesis Testing
Hou, Likun; de la Torre, Jimmy; Nandakumar, Ratna – Journal of Educational Measurement, 2014
Analyzing examinees' responses using cognitive diagnostic models (CDMs) has the advantage of providing diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this article, the Wald test is proposed to examine DIF in the context of CDMs. This study…
Descriptors: Test Bias, Models, Simulation, Error Patterns
Andjelic, Svetlana; Cekerevac, Zoran – Education and Information Technologies, 2014
This article presents the original model of the computer adaptive testing and grade formation, based on scientifically recognized theories. The base of the model is a personalized algorithm for selection of questions depending on the accuracy of the answer to the previous question. The test is divided into three basic levels of difficulty, and the…
Descriptors: Computer Assisted Testing, Educational Technology, Grades (Scholastic), Test Construction
Peer reviewedRoussos, Louis; Stout, William – Applied Psychological Measurement, 1996
A multidimensionality-based differential item functioning (DIF) analysis paradigm is presented that unifies substantive and statistical DIF analysis approaches by linking both to a theoretically sound and mathematically rigorous multidimensional DIF conceptualization. This approach results in the potential for DIF analysis more closely integrated…
Descriptors: Cluster Analysis, Estimation (Mathematics), Hypothesis Testing, Identification
Revuelta, Javier – Journal of Educational and Behavioral Statistics, 2004
This article presents a psychometric model for estimating ability and item-selection strategies in self-adapted testing. In contrast to computer adaptive testing, in self-adapted testing the examinees are allowed to select the difficulty of the items. The item-selection strategy is defined as the distribution of difficulty conditional on the…
Descriptors: Psychometrics, Adaptive Testing, Test Items, Evaluation Methods
Lievens, Filip; Sackett, Paul R. – Journal of Applied Psychology, 2007
This study used principles underlying item generation theory to posit competing perspectives about which features of situational judgment tests might enhance or impede consistent measurement across repeat test administrations. This led to 3 alternate-form development approaches (random assignment, incident isomorphism, and item isomorphism). The…
Descriptors: Validity, High Stakes Tests, Test Construction, Testing
Hula, William; Doyle, Patrick J.; McNeil, Malcolm R.; Mikolic, Joseph M. – Journal of Speech, Language, and Hearing Research, 2006
The purpose of this research was to examine the validity of the 55-item Revised Token Test (RTT) and to compare traditional and Rasch-based scores in their ability to detect group differences and change over time. The 55-item RTT was administered to 108 left- and right-hemisphere stroke survivors, and the data were submitted to Rasch analysis.…
Descriptors: Test Items, Brain Hemisphere Functions, Individual Differences, Difficulty Level

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