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Raykov, Tenko; Marcoulides, George A.; Huber, Chuck – Measurement: Interdisciplinary Research and Perspectives, 2020
It is demonstrated that the popular three-parameter logistic model can lead to markedly inaccurate individual ability level estimates for mixture populations. A theoretically and empirically important setting is initially considered where (a) in one of two subpopulations (latent classes) the two-parameter logistic model holds for each item in a…
Descriptors: Item Response Theory, Models, Measurement Techniques, Item Analysis
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Wind, Stefanie A. – Measurement: Interdisciplinary Research and Perspectives, 2020
A major challenge in the widespread application of Mokken scale analysis (MSA) to educational performance assessments is the requirement of complete data, where every rater rates every student. In this study, simulated and real data are used to demonstrate a method by which researchers and practitioners can apply MSA to incomplete rating designs.…
Descriptors: Item Response Theory, Scaling, Nonparametric Statistics, Performance Based Assessment
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Hancock, Gregory R.; An, Ji – Measurement: Interdisciplinary Research and Perspectives, 2020
As an alternative to Cronbach's [alpha] for estimating scale reliability, McDonald's [omega] has attracted increased attention within the methodological community for its less stringent measurement assumptions. Notwithstanding, [omega] is still seldom used by practitioners, likely due to its unavailability in popular software packages (e.g., SPSS)…
Descriptors: Evaluation, Alternative Assessment, Reliability, Test Reliability
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Chung, Seungwon; Houts, Carrie – Measurement: Interdisciplinary Research and Perspectives, 2020
Advanced modeling of item response data through the item response theory (IRT) or item factor analysis frameworks is becoming increasingly popular. In the social and behavioral sciences, the underlying structure of tests/assessments is often multidimensional (i.e., more than 1 latent variable/construct is represented in the items). This review…
Descriptors: Item Response Theory, Evaluation Methods, Models, Factor Analysis
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Choi, Youn-Jeng; Asilkalkan, Abdullah – Measurement: Interdisciplinary Research and Perspectives, 2019
About 45 R packages to analyze data using item response theory (IRT) have been developed over the last decade. This article introduces these 45 R packages with their descriptions and features. It also describes possible advanced IRT models using R packages, as well as dichotomous and polytomous IRT models, and R packages that contain applications…
Descriptors: Item Response Theory, Data Analysis, Computer Software, Test Bias
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Marcoulides, Katerina M. – Measurement: Interdisciplinary Research and Perspectives, 2019
Longitudinal data analysis has received widespread interest throughout educational, behavioral, and social science research, with latent growth curve modeling currently being one of the most popular methods of analysis. Despite the popularity of latent growth curve modeling, limited attention has been directed toward understanding the issues of…
Descriptors: Reliability, Longitudinal Studies, Growth Models, Structural Equation Models
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Schumacker, Randall – Measurement: Interdisciplinary Research and Perspectives, 2019
The R software provides packages and functions that provide data analysis in classical true score, generalizability theory, item response theory, and Rasch measurement theories. A brief list of notable articles in each measurement theory and the first measurement journals is followed by a list of R psychometric software packages. Each psychometric…
Descriptors: Psychometrics, Computer Software, Measurement, Item Response Theory
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Peabody, Michael R.; Wind, Stefanie A. – Measurement: Interdisciplinary Research and Perspectives, 2019
Differential Item Functioning (DIF) detection procedures provide validity evidence for proposed interpretations of test scores that can help researchers and practitioners ensure that test scores are free from potential bias, and that individual items do not create an advantage for any subgroup of examinees over another. In this study, we use the…
Descriptors: Item Response Theory, Test Items, Scores, Testing
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Luo, Yong; Liang, Xinya – Measurement: Interdisciplinary Research and Perspectives, 2019
Current methods that simultaneously model differential testlet functioning (DTLF) and differential item functioning (DIF) constrain the variances of latent ability and testlet effects to be equal between the focal and the reference groups. Such a constraint can be stringent and unrealistic with real data. In this study, we propose a multigroup…
Descriptors: Test Items, Item Response Theory, Test Bias, Models
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Sen, Sedat; Cohen, Allan S. – Measurement: Interdisciplinary Research and Perspectives, 2019
Mixture item response theory (MixIRT) models combine IRT models with latent class model and assume that there exist latent subpopulations in the data. Identification of latent subpopulations via MixIRT models produces more detailed information. Detailed information about the response processing of examinees provides a better understanding of the…
Descriptors: Item Response Theory, Models, Item Analysis, Personality Traits
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Sheng, Yanyan – Measurement: Interdisciplinary Research and Perspectives, 2019
Classical approach to test theory has been the foundation for educational and psychological measurement for over 90 years. This approach concerns with measurement error and hence test reliability, which in part relies on individual test items. The CTT package, developed in light of this, provides functions for test- and item-level analyses of…
Descriptors: Item Response Theory, Test Reliability, Item Analysis, Error of Measurement
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Raykov, Tenko; Marcoulides, George A.; Harrison, Michael – Measurement: Interdisciplinary Research and Perspectives, 2019
Utilizing the perspective of finite mixture modeling, this note considers whether a finding of a plausible one-parameter logistic model could be spurious for a population with substantial unobserved heterogeneity. A theoretically and empirically important setting is discussed involving the mixture of two latent classes, with the less restrictive…
Descriptors: Models, Evaluation Methods, Social Science Research, Statistical Analysis
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Olvera Astivia, Oscar L.; Zumbo, Bruno D. – Measurement: Interdisciplinary Research and Perspectives, 2019
Methods to generate random correlation matrices have been proposed in the literature, but very few instances exist where these correlation matrices are structured or where the statistical properties of the algorithms are known. By relying on the tetrad relation discovered by Spearman and the properties of the beta distribution, an algorithm is…
Descriptors: Correlation, Psychometrics, Benchmarking, Evaluation Methods
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Zhou, Yuchun – Measurement: Interdisciplinary Research and Perspectives, 2019
Using mixed methods to develop new scales is not a new idea since the 2000s. However, there exists inadequate literature that discusses scale development using mixed methods, with steps including how to design the study, how to implement the process, and how to conduct validation. This study proposes a hands-on model of using mixed methods to…
Descriptors: Mixed Methods Research, Test Construction, Construct Validity, Psychometrics
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Gan, Zhengdong; Hoi, Cathy; Schumacker, Randall – Measurement: Interdisciplinary Research and Perspectives, 2019
While assessment for learning (AfL) has been strongly promulgated by an increasing number of education systems internationally, little research is available that investigates students' responses to such AfL innovations, particularly in a Chinese learning context. There is a need to research and evaluate the AfL practices introduced and their…
Descriptors: College Students, Cognitive Style, Foreign Countries, Educational Practices
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