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Showing 1 to 15 of 111 results Save | Export
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Güler Yavuz Temel – Journal of Educational Measurement, 2024
The purpose of this study was to investigate multidimensional DIF with a simple and nonsimple structure in the context of multidimensional Graded Response Model (MGRM). This study examined and compared the performance of the IRT-LR and Wald test using MML-EM and MHRM estimation approaches with different test factors and test structures in…
Descriptors: Computation, Multidimensional Scaling, Item Response Theory, Models
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Gorney, Kylie; Wollack, James A. – Journal of Educational Measurement, 2023
In order to detect a wide range of aberrant behaviors, it can be useful to incorporate information beyond the dichotomous item scores. In this paper, we extend the l[subscript z] and l*[subscript z] person-fit statistics so that unusual behavior in item scores and unusual behavior in item distractors can be used as indicators of aberrance. Through…
Descriptors: Test Items, Scores, Goodness of Fit, Statistics
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Chen, Chia-Wen; Andersson, Björn; Zhu, Jinxin – Journal of Educational Measurement, 2023
The certainty of response index (CRI) measures respondents' confidence level when answering an item. In conjunction with the answers to the items, previous studies have used descriptive statistics and arbitrary thresholds to identify student knowledge profiles with the CRIs. Whereas this approach overlooked the measurement error of the observed…
Descriptors: Item Response Theory, Factor Analysis, Psychometrics, Test Items
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Guo, Jinxin; Xu, Xin; Xin, Tao – Journal of Educational Measurement, 2023
Missingness due to not-reached items and omitted items has received much attention in the recent psychometric literature. Such missingness, if not handled properly, would lead to biased parameter estimation, as well as inaccurate inference of examinees, and further erode the validity of the test. This paper reviews some commonly used IRT based…
Descriptors: Psychometrics, Bias, Error of Measurement, Test Validity
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Wang, Shaojie; Zhang, Minqiang; Lee, Won-Chan; Huang, Feifei; Li, Zonglong; Li, Yixing; Yu, Sufang – Journal of Educational Measurement, 2022
Traditional IRT characteristic curve linking methods ignore parameter estimation errors, which may undermine the accuracy of estimated linking constants. Two new linking methods are proposed that take into account parameter estimation errors. The item- (IWCC) and test-information-weighted characteristic curve (TWCC) methods employ weighting…
Descriptors: Item Response Theory, Error of Measurement, Accuracy, Monte Carlo Methods
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Almehrizi, Rashid S. – Journal of Educational Measurement, 2021
Estimates of various variance components, universe score variance, measurement error variances, and generalizability coefficients, like all statistics, are subject to sampling variability, particularly in small samples. Such variability is quantified traditionally through estimated standard errors and/or confidence intervals. The paper derived new…
Descriptors: Error of Measurement, Statistics, Design, Generalizability Theory
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Hong, Seong Eun; Monroe, Scott; Falk, Carl F. – Journal of Educational Measurement, 2020
In educational and psychological measurement, a person-fit statistic (PFS) is designed to identify aberrant response patterns. For parametric PFSs, valid inference depends on several assumptions, one of which is that the item response theory (IRT) model is correctly specified. Previous studies have used empirical data sets to explore the effects…
Descriptors: Educational Testing, Psychological Testing, Goodness of Fit, Error of Measurement
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Lee, Sunbok – Journal of Educational Measurement, 2020
In the logistic regression (LR) procedure for differential item functioning (DIF), the parameters of LR have often been estimated using maximum likelihood (ML) estimation. However, ML estimation suffers from the finite-sample bias. Furthermore, ML estimation for LR can be substantially biased in the presence of rare event data. The bias of ML…
Descriptors: Regression (Statistics), Test Bias, Maximum Likelihood Statistics, Simulation
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Liu, Chunyan; Kolen, Michael J. – Journal of Educational Measurement, 2020
Smoothing is designed to yield smoother equating results that can reduce random equating error without introducing very much systematic error. The main objective of this study is to propose a new statistic and to compare its performance to the performance of the Akaike information criterion and likelihood ratio chi-square difference statistics in…
Descriptors: Equated Scores, Statistical Analysis, Error of Measurement, Criteria
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Clauser, Brian E.; Kane, Michael; Clauser, Jerome C. – Journal of Educational Measurement, 2020
An Angoff standard setting study generally yields judgments on a number of items by a number of judges (who may or may not be nested in panels). Variability associated with judges (and possibly panels) contributes error to the resulting cut score. The variability associated with items plays a more complicated role. To the extent that the mean item…
Descriptors: Cutting Scores, Generalization, Decision Making, Standard Setting
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Kim, Stella Y.; Lee, Won-Chan – Journal of Educational Measurement, 2020
The current study aims to evaluate the performance of three non-IRT procedures (i.e., normal approximation, Livingston-Lewis, and compound multinomial) for estimating classification indices when the observed score distribution shows atypical patterns: (a) bimodality, (b) structural (i.e., systematic) bumpiness, or (c) structural zeros (i.e., no…
Descriptors: Classification, Accuracy, Scores, Cutting Scores
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Lee, Won-Chan; Kim, Stella Y.; Choi, Jiwon; Kang, Yujin – Journal of Educational Measurement, 2020
This article considers psychometric properties of composite raw scores and transformed scale scores on mixed-format tests that consist of a mixture of multiple-choice and free-response items. Test scores on several mixed-format tests are evaluated with respect to conditional and overall standard errors of measurement, score reliability, and…
Descriptors: Raw Scores, Item Response Theory, Test Format, Multiple Choice Tests
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Tijmstra, Jesper; Bolsinova, Maria; Liaw, Yuan-Ling; Rutkowski, Leslie; Rutkowski, David – Journal of Educational Measurement, 2020
Although the root-mean squared deviation (RMSD) is a popular statistical measure for evaluating country-specific item-level misfit (i.e., differential item functioning [DIF]) in international large-scale assessment, this paper shows that its sensitivity to detect misfit may depend strongly on the proficiency distribution of the considered…
Descriptors: Test Items, Goodness of Fit, Probability, Accuracy
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Kim, Hyung Jin; Brennan, Robert L.; Lee, Won-Chan – Journal of Educational Measurement, 2020
In equating, smoothing techniques are frequently used to diminish sampling error. There are typically two types of smoothing: presmoothing and postsmoothing. For polynomial log-linear presmoothing, an optimum smoothing degree can be determined statistically based on the Akaike information criterion or Chi-square difference criterion. For…
Descriptors: Equated Scores, Sampling, Error of Measurement, Statistical Analysis
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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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