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Showing 76 to 90 of 1,153 results Save | Export
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Lee, Chansoon; Qian, Hong – Educational and Psychological Measurement, 2022
Using classical test theory and item response theory, this study applied sequential procedures to a real operational item pool in a variable-length computerized adaptive testing (CAT) to detect items whose security may be compromised. Moreover, this study proposed a hybrid threshold approach to improve the detection power of the sequential…
Descriptors: Computer Assisted Testing, Adaptive Testing, Licensing Examinations (Professions), Item Response Theory
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Jin, Kuan-Yu; Eckes, Thomas – Educational and Psychological Measurement, 2022
Performance assessments heavily rely on human ratings. These ratings are typically subject to various forms of error and bias, threatening the assessment outcomes' validity and fairness. Differential rater functioning (DRF) is a special kind of threat to fairness manifesting itself in unwanted interactions between raters and performance- or…
Descriptors: Performance Based Assessment, Rating Scales, Test Bias, Student Evaluation
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Wind, Stefanie A. – Educational and Psychological Measurement, 2022
Researchers frequently use Mokken scale analysis (MSA), which is a nonparametric approach to item response theory, when they have relatively small samples of examinees. Researchers have provided some guidance regarding the minimum sample size for applications of MSA under various conditions. However, these studies have not focused on item-level…
Descriptors: Nonparametric Statistics, Item Response Theory, Sample Size, Test Items
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Dimitrov, Dimiter M. – Educational and Psychological Measurement, 2022
Proposed is a new method of standard setting referred to as response vector for mastery (RVM) method. Under the RVM method, the task of panelists that participate in the standard setting process does not involve conceptualization of a borderline examinee and probability judgments as it is the case with the Angoff and bookmark methods. Also, the…
Descriptors: Standard Setting (Scoring), Cutting Scores, Computation, Mastery Learning
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Jiang, Zhehan; Raymond, Mark; DiStefano, Christine; Shi, Dexin; Liu, Ren; Sun, Junhua – Educational and Psychological Measurement, 2022
Computing confidence intervals around generalizability coefficients has long been a challenging task in generalizability theory. This is a serious practical problem because generalizability coefficients are often computed from designs where some facets have small sample sizes, and researchers have little guide regarding the trustworthiness of the…
Descriptors: Monte Carlo Methods, Intervals, Generalizability Theory, Error of Measurement
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Lee, Sooyong; Han, Suhwa; Choi, Seung W. – Educational and Psychological Measurement, 2022
Response data containing an excessive number of zeros are referred to as zero-inflated data. When differential item functioning (DIF) detection is of interest, zero-inflation can attenuate DIF effects in the total sample and lead to underdetection of DIF items. The current study presents a DIF detection procedure for response data with excess…
Descriptors: Test Bias, Monte Carlo Methods, Simulation, Models
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Cooperman, Allison W.; Weiss, David J.; Wang, Chun – Educational and Psychological Measurement, 2022
Adaptive measurement of change (AMC) is a psychometric method for measuring intra-individual change on one or more latent traits across testing occasions. Three hypothesis tests--a Z test, likelihood ratio test, and score ratio index--have demonstrated desirable statistical properties in this context, including low false positive rates and high…
Descriptors: Error of Measurement, Psychometrics, Hypothesis Testing, Simulation
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Brennan, Robert L.; Kim, Stella Y.; Lee, Won-Chan – Educational and Psychological Measurement, 2022
This article extends multivariate generalizability theory (MGT) to tests with different random-effects designs for each level of a fixed facet. There are numerous situations in which the design of a test and the resulting data structure are not definable by a single design. One example is mixed-format tests that are composed of multiple-choice and…
Descriptors: Multivariate Analysis, Generalizability Theory, Multiple Choice Tests, Test Construction
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Weese, James D.; Turner, Ronna C.; Ames, Allison; Crawford, Brandon; Liang, Xinya – Educational and Psychological Measurement, 2022
A simulation study was conducted to investigate the heuristics of the SIBTEST procedure and how it compares with ETS classification guidelines used with the Mantel-Haenszel procedure. Prior heuristics have been used for nearly 25 years, but they are based on a simulation study that was restricted due to computer limitations and that modeled item…
Descriptors: Test Bias, Heuristics, Classification, Statistical Analysis
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Soland, James – Educational and Psychological Measurement, 2022
Considerable thought is often put into designing randomized control trials (RCTs). From power analyses and complex sampling designs implemented preintervention to nuanced quasi-experimental models used to estimate treatment effects postintervention, RCT design can be quite complicated. Yet when psychological constructs measured using survey scales…
Descriptors: Item Response Theory, Surveys, Scoring, Randomized Controlled Trials
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Menold, Natalja; Raykov, Tenko – Educational and Psychological Measurement, 2022
The possible dependency of criterion validity on item formulation in a multicomponent measuring instrument is examined. The discussion is concerned with evaluation of the differences in criterion validity between two or more groups (populations/subpopulations) that have been administered instruments with items having differently formulated item…
Descriptors: Test Items, Measures (Individuals), Test Validity, Difficulty Level
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Guastadisegni, Lucia; Cagnone, Silvia; Moustaki, Irini; Vasdekis, Vassilis – Educational and Psychological Measurement, 2022
This article studies the Type I error, false positive rates, and power of four versions of the Lagrange multiplier test to detect measurement noninvariance in item response theory (IRT) models for binary data under model misspecification. The tests considered are the Lagrange multiplier test computed with the Hessian and cross-product approach,…
Descriptors: Measurement, Statistical Analysis, Item Response Theory, Test Items
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Fu, Yuanshu; Wen, Zhonglin; Wang, Yang – Educational and Psychological Measurement, 2022
Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is…
Descriptors: Comparative Analysis, Structural Equation Models, Factor Analysis, Reliability
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Ames, Allison J. – Educational and Psychological Measurement, 2022
Individual response style behaviors, unrelated to the latent trait of interest, may influence responses to ordinal survey items. Response style can introduce bias in the total score with respect to the trait of interest, threatening valid interpretation of scores. Despite claims of response style stability across scales, there has been little…
Descriptors: Response Style (Tests), Individual Differences, Scores, Test Items
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Man, Kaiwen; Schumacker, Randall; Morell, Monica; Wang, Yurou – Educational and Psychological Measurement, 2022
While hierarchical linear modeling is often used in social science research, the assumption of normally distributed residuals at the individual and cluster levels can be violated in empirical data. Previous studies have focused on the effects of nonnormality at either lower or higher level(s) separately. However, the violation of the normality…
Descriptors: Hierarchical Linear Modeling, Statistical Distributions, Statistical Bias, Computation
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