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Wenchao Ma; Miguel A. Sorrel; Xiaoming Zhai; Yuan Ge – Journal of Educational Measurement, 2024
Most existing diagnostic models are developed to detect whether students have mastered a set of skills of interest, but few have focused on identifying what scientific misconceptions students possess. This article developed a general dual-purpose model for simultaneously estimating students' overall ability and the presence and absence of…
Descriptors: Models, Misconceptions, Diagnostic Tests, Ability
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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
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Wind, Stefanie A.; Sebok-Syer, Stefanie S. – Journal of Educational Measurement, 2019
When practitioners use modern measurement models to evaluate rating quality, they commonly examine rater fit statistics that summarize how well each rater's ratings fit the expectations of the measurement model. Essentially, this approach involves examining the unexpected ratings that each misfitting rater assigned (i.e., carrying out analyses of…
Descriptors: Measurement, Models, Evaluators, Simulation
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Feuerstahler, Leah; Wilson, Mark – Journal of Educational Measurement, 2019
Scores estimated from multidimensional item response theory (IRT) models are not necessarily comparable across dimensions. In this article, the concept of aligned dimensions is formalized in the context of Rasch models, and two methods are described--delta dimensional alignment (DDA) and logistic regression alignment (LRA)--to transform estimated…
Descriptors: Item Response Theory, Models, Scores, Comparative Analysis
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Drabinová, Adéla; Martinková, Patrícia – Journal of Educational Measurement, 2017
In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…
Descriptors: Test Items, Regression (Statistics), Guessing (Tests), Identification
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Liu, Chen-Wei; Wang, Wen-Chung – Journal of Educational Measurement, 2017
The examinee-selected-item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set of items (e.g., choose one item to respond from a pair of items), always yields incomplete data (i.e., only the selected items are answered and the others have missing data) that are likely nonignorable. Therefore, using…
Descriptors: Item Response Theory, Models, Maximum Likelihood Statistics, Data Analysis
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Guo, Rui; Zheng, Yi; Chang, Hua-Hua – Journal of Educational Measurement, 2015
An important assumption of item response theory is item parameter invariance. Sometimes, however, item parameters are not invariant across different test administrations due to factors other than sampling error; this phenomenon is termed item parameter drift. Several methods have been developed to detect drifted items. However, most of the…
Descriptors: Item Response Theory, Test Items, Evaluation Methods, Equated Scores
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Lee, Soo; Suh, Youngsuk – Journal of Educational Measurement, 2018
Lord's Wald test for differential item functioning (DIF) has not been studied extensively in the context of the multidimensional item response theory (MIRT) framework. In this article, Lord's Wald test was implemented using two estimation approaches, marginal maximum likelihood estimation and Bayesian Markov chain Monte Carlo estimation, to detect…
Descriptors: Item Response Theory, Sample Size, Models, Error of Measurement
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Häggström, Jenny; Wiberg, Marie – Journal of Educational Measurement, 2014
The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent…
Descriptors: Equated Scores, Data Analysis, Comparative Analysis, Simulation
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Shin, Hyo Jeong; Wilson, Mark; Choi, In-Hee – Journal of Educational Measurement, 2017
This study proposes a structured constructs model (SCM) to examine measurement in the context of a multidimensional learning progression (LP). The LP is assumed to have features that go beyond a typical multidimentional IRT model, in that there are hypothesized to be certain cross-dimensional linkages that correspond to requirements between the…
Descriptors: Middle School Students, Student Evaluation, Measurement Techniques, Learning Processes
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Wilson, Mark; Gochyyev, Perman; Scalise, Kathleen – Journal of Educational Measurement, 2017
This article summarizes assessment of cognitive skills through collaborative tasks, using field test results from the Assessment and Teaching of 21st Century Skills (ATC21S) project. This project, sponsored by Cisco, Intel, and Microsoft, aims to help educators around the world enable students with the skills to succeed in future career and…
Descriptors: Cognitive Ability, Thinking Skills, Evaluation Methods, Educational Assessment
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Suh, Youngsuk; Bolt, Daniel M. – Journal of Educational Measurement, 2011
In multiple-choice items, differential item functioning (DIF) in the correct response may or may not be caused by differentially functioning distractors. Identifying distractors as causes of DIF can provide valuable information for potential item revision or the design of new test items. In this paper, we examine a two-step approach based on…
Descriptors: Test Items, Test Bias, Multiple Choice Tests, Simulation
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Bolt, Daniel M.; Gierl, Mark J. – Journal of Educational Measurement, 2006
Inspection of differential item functioning (DIF) in translated test items can be informed by graphical comparisons of item response functions (IRFs) across translated forms. Due to the many forms of DIF that can emerge in such analyses, it is important to develop statistical tests that can confirm various characteristics of DIF when present.…
Descriptors: Regression (Statistics), Tests, Test Bias, Test Items
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Birenbaum, Menucha; Tatsuoka, Kikumi – Journal of Educational Measurement, 1982
Empirical results from two studies--a simulation study and an experimental one--indicated that, in achievement data of the problem-solving type where a specific subject matter area is being tested, the greater the variety of the algorithms used, the higher the dimensionality of the test data. (Author/PN)
Descriptors: Achievement Tests, Algorithms, Data Analysis, Factor Structure