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Showing 1 to 15 of 29 results Save | Export
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Ferrando, Pere J.; Lorenzo-Seva, Urbano – Educational and Psychological Measurement, 2021
Unit-weight sum scores (UWSSs) are routinely used as estimates of factor scores on the basis of solutions obtained with the nonlinear exploratory factor analysis (EFA) model for ordered-categorical responses. Theoretically, this practice results in a loss of information and accuracy, and is expected to lead to biased estimates. However, the…
Descriptors: Scores, Factor Analysis, Automation, Fidelity
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Goretzko, David – Educational and Psychological Measurement, 2022
Determining the number of factors in exploratory factor analysis is arguably the most crucial decision a researcher faces when conducting the analysis. While several simulation studies exist that compare various so-called factor retention criteria under different data conditions, little is known about the impact of missing data on this process.…
Descriptors: Factor Analysis, Research Problems, Data, Prediction
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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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Pere J. Ferrando; David Navarro-González; Fabia Morales-Vives – Educational and Psychological Measurement, 2025
The problem of local item dependencies (LIDs) is very common in personality and attitude measures, particularly in those that measure narrow-bandwidth dimensions. At the structural level, these dependencies can be modeled by using extended factor analytic (FA) solutions that include correlated residuals. However, the effects that LIDs have on the…
Descriptors: Scores, Accuracy, Evaluation Methods, Factor Analysis
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PaaBen, Benjamin; Dywel, Malwina; Fleckenstein, Melanie; Pinkwart, Niels – International Educational Data Mining Society, 2022
Item response theory (IRT) is a popular method to infer student abilities and item difficulties from observed test responses. However, IRT struggles with two challenges: How to map items to skills if multiple skills are present? And how to infer the ability of new students that have not been part of the training data? Inspired by recent advances…
Descriptors: Item Response Theory, Test Items, Item Analysis, Inferences
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Baris Pekmezci, Fulya; Gulleroglu, H. Deniz – Eurasian Journal of Educational Research, 2019
Purpose: This study aims to investigate the orthogonality assumption, which restricts the use of Bifactor item response theory under different conditions. Method: Data of the study have been obtained in accordance with the Bifactor model. It has been produced in accordance with two different models (Model 1 and Model 2) in a simulated way.…
Descriptors: Item Response Theory, Accuracy, Item Analysis, Correlation
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Fillauer, Jonathan Parks; Bolden, Jennifer; Jacobson, Melanie; Partlow, Brock H.; Benavides, Andrea; Shultz, Jessica N. – Applied Cognitive Psychology, 2020
The present study attempts to expand our understanding of frustration, clinical symptoms, and working memory by examining the unique contribution of attention-deficit/hyperactivity disorder symptoms and frustration to working memory capacity (WMC). A factor-analytic framework was utilized to isolate and examine WMC based on results from three…
Descriptors: Accuracy, Short Term Memory, Psychological Patterns, Factor Analysis
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Green, Samuel; Xu, Yuning; Thompson, Marilyn S. – Educational and Psychological Measurement, 2018
Parallel analysis (PA) assesses the number of factors in exploratory factor analysis. Traditionally PA compares the eigenvalues for a sample correlation matrix with the eigenvalues for correlation matrices for 100 comparison datasets generated such that the variables are independent, but this approach uses the wrong reference distribution. The…
Descriptors: Factor Analysis, Accuracy, Statistical Distributions, Comparative Analysis
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Dai, Ting; Du, Yang; Cromley, Jennifer G.; Fechter, Tia M.; Nelson, Frank – AERA Online Paper Repository, 2019
Certain planned-missing designs (e.g., simple-matrix sampling) cause zero covariances between variables not jointly observed, making it impossible to do analyses beyond mean estimations without specialized analyses. We tested a multigroup confirmatory factor analysis (CFA) approach by Cudeck (2000), which obtains a model-estimated…
Descriptors: Factor Analysis, Educational Research, Research Design, Data Analysis
George Clinton Denison – ProQuest LLC, 2024
Enabling learners to successfully use their second language (L2) in meaningful ways is a critical goal of instruction. Ultimately, most learners want to meet the L2 demands of the contexts in which they will use the language. To accomplish this, learners must develop linguistic knowledge and apply it in a manner that is contextually appropriate…
Descriptors: Writing Evaluation, English (Second Language), Second Language Learning, Second Language Instruction
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de Zubicaray, Greig I.; Arciuli, Joanne; Kearney, Elaine; Guenther, Frank; McMahon, Katie L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
Grounded or embodied cognition research has employed body-object interaction (BOI; e.g., Pexman et al., 2019) ratings to investigate sensorimotor effects during language processing. We investigated relationships between BOI ratings and nonarbitrary statistical mappings between words' phonological forms and their syntactic category in English;…
Descriptors: Language Processing, Psychomotor Skills, English, Predictor Variables
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Green, Samuel B.; Redell, Nickalus; Thompson, Marilyn S.; Levy, Roy – Educational and Psychological Measurement, 2016
Parallel analysis (PA) is a useful empirical tool for assessing the number of factors in exploratory factor analysis. On conceptual and empirical grounds, we argue for a revision to PA that makes it more consistent with hypothesis testing. Using Monte Carlo methods, we evaluated the relative accuracy of the revised PA (R-PA) and traditional PA…
Descriptors: Accuracy, Factor Analysis, Hypothesis Testing, Monte Carlo Methods
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Yan, Xun; Kim, Ha Ram; Kim, Ji Young – Language Testing, 2021
Speech fluency has been extensively researched as a core construct for second language (L2) speaking assessment. Despite the broad consensus on its multifaceted nature, few researchers have empirically explored the dimensionality of this construct. Operationalizations of fluency vary across research and practice, using both holistic and…
Descriptors: Language Fluency, Language Tests, Accuracy, Speech Communication
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Sahin, Alper; Anil, Duygu – Educational Sciences: Theory and Practice, 2017
This study investigates the effects of sample size and test length on item-parameter estimation in test development utilizing three unidimensional dichotomous models of item response theory (IRT). For this purpose, a real language test comprised of 50 items was administered to 6,288 students. Data from this test was used to obtain data sets of…
Descriptors: Test Length, Sample Size, Item Response Theory, Test Construction
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Farmer, Ryan L.; Floyd, Randy G.; Reynolds, Matthew R.; Kranzler, John H. – Psychology in the Schools, 2014
The most global score yielded by intelligence tests, IQs, are supported by substantial validity evidence and have historically been central to the identification of intellectual disabilities, learning disabilities, and giftedness. This study examined the extent to which IQs measure the ability they target, psychometric "g." Data from…
Descriptors: Intelligence Quotient, Factor Analysis, Intelligence Tests, Psychometrics
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