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Conrad Borchers – International Educational Data Mining Society, 2025
Algorithmic bias is a pressing concern in educational data mining (EDM), as it risks amplifying inequities in learning outcomes. The Area Between ROC Curves (ABROCA) metric is frequently used to measure discrepancies in model performance across demographic groups to quantify overall model fairness. However, its skewed distribution--especially when…
Descriptors: Algorithms, Bias, Statistics, Simulation
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Ravand, Hamdollah; Baghaei, Purya – International Journal of Testing, 2020
More than three decades after their introduction, diagnostic classification models (DCM) do not seem to have been implemented in educational systems for the purposes they were devised. Most DCM research is either methodological for model development and refinement or retrofitting to existing nondiagnostic tests and, in the latter case, basically…
Descriptors: Classification, Models, Diagnostic Tests, Test Construction
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Nicewander, W. Alan – Educational and Psychological Measurement, 2018
Spearman's correction for attenuation (measurement error) corrects a correlation coefficient for measurement errors in either-or-both of two variables, and follows from the assumptions of classical test theory. Spearman's equation removes all measurement error from a correlation coefficient which translates into "increasing the reliability of…
Descriptors: Error of Measurement, Correlation, Sample Size, Computation
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Retnaningsih, Woro; Djatmiko; Sumarlam – English Language Teaching, 2017
The research objective is to develop a model of Assessment for Learning (AFL) in Pragmatic course in IAIN Surakarta. The research problems are as follows: How did the lecturer develop a model of AFL? What was the form of assessment information used as the model of AFL? How was the results of the implementation of the model of assessment. The…
Descriptors: Pragmatics, Educational Quality, College Faculty, English (Second Language)
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Jackson, Dennis L.; Voth, Jennifer; Frey, Marc P. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Determining an appropriate sample size for use in latent variable modeling techniques has presented ongoing challenges to researchers. In particular, small sample sizes are known to present concerns over sampling error for the variances and covariances on which model estimation is based, as well as for fit indexes and convergence failures. The…
Descriptors: Sample Size, Factor Analysis, Measurement, Models
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Hula, William D.; Fergadiotis, Gerasimos; Martin, Nadine – American Journal of Speech-Language Pathology, 2012
Purpose: The purpose of this study was to identify the most appropriate item response theory (IRT) measurement model for aphasia tests requiring 2-choice responses and to determine whether small samples are adequate for estimating such models. Method: Pyramids and Palm Trees (Howard & Patterson, 1992) test data that had been collected from…
Descriptors: Sample Size, Guessing (Tests), Aphasia, Item Response Theory
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Wanstrom, Linda – Multivariate Behavioral Research, 2009
Second-order latent growth curve models (S. C. Duncan & Duncan, 1996; McArdle, 1988) can be used to study group differences in change in latent constructs. We give exact formulas for the covariance matrix of the parameter estimates and an algebraic expression for the estimation of slope differences. Formulas for calculations of the required sample…
Descriptors: Sample Size, Effect Size, Mathematical Formulas, Computation
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Bodkin-Andrews, Gawaian H.; Ha, My Trinh; Craven, Rhonda G.; Yeung, Alexander Seesing – International Journal of Testing, 2010
This investigation reports on the cross-cultural equivalence testing of the Self-Description Questionnaire II (short version; SDQII-S) for Indigenous and non-Indigenous Australian secondary student samples. A variety of statistical analysis techniques were employed to assess the psychometric properties of the SDQII-S for both the Indigenous and…
Descriptors: Indigenous Populations, Disadvantaged, Testing, Measures (Individuals)
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Gagne, Phill; Hancock, Gregory R. – Multivariate Behavioral Research, 2006
Sample size recommendations in confirmatory factor analysis (CFA) have recently shifted away from observations per variable or per parameter toward consideration of model quality. Extending research by Marsh, Hau, Balla, and Grayson (1998), simulations were conducted to determine the extent to which CFA model convergence and parameter estimation…
Descriptors: Sample Size, Factor Analysis, Computation, Models
Parshall, Cynthia G.; Kromrey, Jeffrey D.; Chason, Walter M. – 1996
The benefits of item response theory (IRT) will only accrue to a testing program to the extent that model assumptions are met. Obtaining accurate item parameter estimates is a critical first step. However, the sample sizes required for stable parameter estimation are often difficult to obtain in practice, particularly for the more complex models.…
Descriptors: Comparative Analysis, Estimation (Mathematics), Item Response Theory, Models
Hutchinson, Susan R. – 1994
The work of R. MacCallum et al. (1992) was extended by examining chance modifications through a Monte Carlo simulation. The stability of post hoc model modifications was examined under varying sample size, model complexity, and severity of misspecification using 2- and 4-factor oblique confirmatory factor analysis (CFA) models with four and eight…
Descriptors: Computer Simulation, Models, Monte Carlo Methods, Reliability
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Hertzog, Christopher; Lindenberger, Ulman; Ghisletta, Paolo; Oertzen, Timo von – Psychological Methods, 2006
We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris…
Descriptors: Multivariate Analysis, Models, Sample Size, Reliability
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Liao, Hui; Chuang, Aichia – Journal of Applied Psychology, 2007
This longitudinal field study integrates the theories of transformational leadership (TFL) and relationship marketing to examine how TFL influences employee service performance and customer relationship outcomes by transforming both (at the micro level) the service employees' attitudes and (at the macro level) the work unit's service climate.…
Descriptors: Employees, Self Efficacy, Transformational Leadership, Leadership