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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
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
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
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
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
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
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
Bulut, Okan; Quo, Qi; Gierl, Mark J. – Large-scale Assessments in Education, 2017
Position effects may occur in both paper--pencil tests and computerized assessments when examinees respond to the same test items located in different positions on the test. To examine position effects in large-scale assessments, previous studies often used multilevel item response models within the generalized linear mixed modeling framework.…
Descriptors: Structural Equation Models, Educational Assessment, Measurement, Test Items
Li, Dongmei; Yi, Qing; Harris, Deborah – ACT, Inc., 2017
In preparation for online administration of the ACT® test, ACT conducted studies to examine the comparability of scores between online and paper administrations, including a timing study in fall 2013, a mode comparability study in spring 2014, and a second mode comparability study in spring 2015. This report presents major findings from these…
Descriptors: College Entrance Examinations, Computer Assisted Testing, Comparative Analysis, Test Format
Shogren, Karrie A.; Wehmeyer, Michael L.; Little, Todd D.; Forber-Pratt, Anjali J.; Palmer, Susan B.; Seo, Hyojeong – Career Development and Transition for Exceptional Individuals, 2017
The purpose of this article is to describe preliminary psychometric characteristics of a student self-report measure of self-determination, the "Self-Determination Inventory: Student Report" version (SDI-SR), designed for youth with and without disabilities. We administered the draft assessment to 311 youth and examined item functioning…
Descriptors: Construct Validity, Test Reliability, Scores, Psychometrics
Han, Kyung T.; Guo, Fanmin – Practical Assessment, Research & Evaluation, 2014
The full-information maximum likelihood (FIML) method makes it possible to estimate and analyze structural equation models (SEM) even when data are partially missing, enabling incomplete data to contribute to model estimation. The cornerstone of FIML is the missing-at-random (MAR) assumption. In (unidimensional) computerized adaptive testing…
Descriptors: Maximum Likelihood Statistics, Structural Equation Models, Data, Computer Assisted Testing
Cheung, Wai Ming; Huang, Yanli; Tsang, Hector W. H. – AERA Online Paper Repository, 2017
Hong Kong attained champion of the PIRLS 2011 that aroused keen interest in understanding the underlying reasons of a non-alphabetic language. The study aimed at unravelling various aspects of the student and home factors which contributed to remarkable Chinese reading performance. Totally 3,875 students from 132 primary schools completed the…
Descriptors: Chinese, Reading Achievement, Elementary School Students, Structural Equation Models
Blömeke, Sigrid; Dunekacke, Simone; Jenßen, Lars – European Early Childhood Education Research Journal, 2017
This study examined the level, structure and cognitive, educational and psychological determinants of beliefs about the relevance and nature of mathematics, about gender-stereotypes with respect to mathematics abilities and about enjoyment of mathematics. Prospective preschool teachers from programs at vocational schools and higher education…
Descriptors: Foreign Countries, Preservice Teachers, Beliefs, Mathematics Education
Sen, Rohini – ProQuest LLC, 2012
In the last five decades, research on the uses of response time has extended into the field of psychometrics (Schnikpe & Scrams, 1999; van der Linden, 2006; van der Linden, 2007), where interest has centered around the usefulness of response time information in item calibration and person measurement within an item response theory. framework.…
Descriptors: Structural Equation Models, Reaction Time, Item Response Theory, Computation
Ferrando, Pere J.; Anguiano-Carrasco, Cristina; Demestre, Josep – Structural Equation Modeling: A Multidisciplinary Journal, 2013
This article proposes a model-based procedure, intended for personality measures, for exploiting the auxiliary information provided by the certainty with which individuals answer every item (response certainty). This information is used to (a) obtain more accurate estimates of individual trait levels, and (b) provide a more detailed assessment of…
Descriptors: Structural Equation Models, Item Response Theory, Personality Measures, Goodness of Fit