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Wu, Sz-Yan; Kang, Hyeon-Ah; Jensen, Jody L. – Measurement in Physical Education and Exercise Science, 2023
The objective was to verify the construct validity and test-retest reliability of the Test of Advanced Movement Skills (TAMS) with an innovative dual-outcome scoring system. Three statistical approaches--confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), and item response theory analysis (IRT)--were applied to the…
Descriptors: Construct Validity, Pretests Posttests, Psychomotor Skills, Scoring
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Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
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Eunsook Kim; Diep Nguyen; Siyu Liu; Yan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Factor mixture modeling (FMM) is generally complex with both unobserved categorical and unobserved continuous variables. We explore the potential of item parceling to reduce the model complexity of FMM and improve convergence and class enumeration accordingly. To this end, we conduct Monte Carlo simulations with three types of data, continuous,…
Descriptors: Structural Equation Models, Factor Analysis, Factor Structure, Monte Carlo Methods
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Zachary J. Roman; Patrick Schmidt; Jason M. Miller; Holger Brandt – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Careless and insufficient effort responding (C/IER) is a situation where participants respond to survey instruments without considering the item content. This phenomena adds noise to data leading to erroneous inference. There are multiple approaches to identifying and accounting for C/IER in survey settings, of these approaches the best performing…
Descriptors: Structural Equation Models, Bayesian Statistics, Response Style (Tests), Robustness (Statistics)
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Xiaying Zheng; Ji Seung Yang; Jeffrey R. Harring – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Measuring change in an educational or psychological construct over time is often achieved by repeatedly administering the same items to the same examinees over time and fitting a second-order latent growth curve model. However, latent growth modeling with full information maximum likelihood (FIML) estimation becomes computationally challenging…
Descriptors: Longitudinal Studies, Data Analysis, Item Response Theory, Structural Equation Models
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Paek, Insu; Cui, Mengyao; Öztürk Gübes, Nese; Yang, Yanyun – Educational and Psychological Measurement, 2018
The purpose of this article is twofold. The first is to provide evaluative information on the recovery of model parameters and their standard errors for the two-parameter item response theory (IRT) model using different estimation methods by Mplus. The second is to provide easily accessible information for practitioners, instructors, and students…
Descriptors: Item Response Theory, Computation, Factor Analysis, Statistical Analysis
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Morell, Monica; Yang, Ji Seung; Gladstone, Jessica R.; Turci Faust, Lara; Ponnock, Annette R.; Lim, Hyo Jin; Wigfield, Allan – Journal of Educational Psychology, 2021
"Grit" is defined as passion and perseverance for achieving long-term goals and consists of two proposed subcomponents: consistency of interests and perseverance of effort. It has become a much-discussed construct even though research on its underlying factor structure has produced inconclusive results. Furthermore, grit as measured by…
Descriptors: Persistence, Goal Orientation, Factor Structure, Predictive Validity
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Toker, Turker; Green, Kathy – International Journal of Assessment Tools in Education, 2021
This study provides a comparison of the results of latent class analysis (LCA) and mixture Rasch model (MRM) analysis using data from the Trends in International Mathematics and Science Study -- 2011 (TIMSS-2011) with a focus on the 8th-grade mathematics section. The research study focuses on the comparison of LCA and MRM to determine if results…
Descriptors: Multivariate Analysis, Structural Equation Models, Item Response Theory, Achievement Tests
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Chung, Seungwon; Cai, Li – Grantee Submission, 2019
The use of item responses from questionnaire data is ubiquitous in social science research. One side effect of using such data is that researchers must often account for item level missingness. Multiple imputation (Rubin, 1987) is one of the most widely used missing data handling techniques. The traditional multiple imputation approach in…
Descriptors: Computation, Statistical Inference, Structural Equation Models, Goodness of Fit
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Hancock, Gregory R.; An, Ji – Educational Measurement: Issues and Practice, 2018
In this ITEMS module, we frame the topic of scale reliability within a "confirmatory factor analysis" and "structural equation modeling" (SEM) context and address some of the limitations of Cronbach's a. This modeling approach has two major advantages: (1) it allows researchers to make explicit the relation between their items…
Descriptors: Reliability, Structural Equation Models, Factor Analysis, Correlation
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Gullo, Dominic F.; Miller, Michel – European Early Childhood Education Research Journal, 2018
Factors that affect children's school readiness potential are evident from birth. Structural equation modeling was used to test the hypotheses that certain factors related to family risk conditions, the quality of prenatal care, maternal health during pregnancy, and the health status of the child at birth mediate children's readiness for school.…
Descriptors: Structural Equation Models, School Readiness, Longitudinal Studies, Surveys
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Kim, Seohyun; Lu, Zhenqiu; Cohen, Allan S. – Measurement: Interdisciplinary Research and Perspectives, 2018
Bayesian algorithms have been used successfully in the social and behavioral sciences to analyze dichotomous data particularly with complex structural equation models. In this study, we investigate the use of the Polya-Gamma data augmentation method with Gibbs sampling to improve estimation of structural equation models with dichotomous variables.…
Descriptors: Bayesian Statistics, Structural Equation Models, Computation, Social Science Research
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Uyar, Seyma – International Journal of Assessment Tools in Education, 2021
In the current study, the appropriateness of the Mathematics Attitude Questionnaire administered to middle school 8th grade students in the TIMSS 2015 application to the exploratory structural equation and confirmatory factor analysis models was examined. The study was conducted on 6079 students making up the sample of Turkey. In the TIMSS 2015…
Descriptors: Factor Structure, Factor Analysis, Achievement Tests, Elementary Secondary Education
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Verhagen, Josje; Boom, Jan; Mulder, Hanna; de Bree, Elise; Leseman, Paul – Developmental Psychology, 2019
The aim of this longitudinal study is to evaluate 3 views on the relationship between nonword repetition and vocabulary: (i) the storage-based view that considers nonword repetition, a measure of phonological storage, as the driving force behind vocabulary development, (ii) the lexical restructuring view that considers improvements in nonword…
Descriptors: Correlation, Word Recognition, Repetition, Vocabulary
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Cai, Yuyang; Kunnan, Antony John – Language Assessment Quarterly, 2018
This study examined the separability of domain-general and domain-specific content knowledge from Language for Specific Purposes (LSP) reading ability. A pool of 1,491 nursing students in China participated by responding to a nursing English test and a nursing knowledge test. Primary data analysis involved four steps: (a) conducting a…
Descriptors: Foreign Countries, Item Response Theory, Structural Equation Models, English for Special Purposes
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