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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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Emma Somer; Carl Falk; Milica Miocevic – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon's correction and…
Descriptors: Scores, Structural Equation Models, Comparative Analysis, Sample Size
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Raykov, Tenko; DiStefano, Christine; Calvocoressi, Lisa; Volker, Martin – Educational and Psychological Measurement, 2022
A class of effect size indices are discussed that evaluate the degree to which two nested confirmatory factor analysis models differ from each other in terms of fit to a set of observed variables. These descriptive effect measures can be used to quantify the impact of parameter restrictions imposed in an initially considered model and are free…
Descriptors: Effect Size, Models, Measurement Techniques, Factor Analysis
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DiStefano, Christine; McDaniel, Heather L.; Zhang, Liyun; Shi, Dexin; Jiang, Zhehan – Educational and Psychological Measurement, 2019
A simulation study was conducted to investigate the model size effect when confirmatory factor analysis (CFA) models include many ordinal items. CFA models including between 15 and 120 ordinal items were analyzed with mean- and variance-adjusted weighted least squares to determine how varying sample size, number of ordered categories, and…
Descriptors: Factor Analysis, Effect Size, Data, Sample Size
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Kelcey, Benjamin; Dong, Nianbo; Spybrook, Jessaca; Cox, Kyle – Journal of Educational and Behavioral Statistics, 2017
Designs that facilitate inferences concerning both the total and indirect effects of a treatment potentially offer a more holistic description of interventions because they can complement "what works" questions with the comprehensive study of the causal connections implied by substantive theories. Mapping the sensitivity of designs to…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Mediation Theory, Models
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Li, Wei; Konstantopoulos, Spyros – Educational and Psychological Measurement, 2017
Field experiments in education frequently assign entire groups such as schools to treatment or control conditions. These experiments incorporate sometimes a longitudinal component where for example students are followed over time to assess differences in the average rate of linear change, or rate of acceleration. In this study, we provide methods…
Descriptors: Educational Experiments, Field Studies, Models, Randomized Controlled Trials
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Koran, Jennifer – Measurement and Evaluation in Counseling and Development, 2016
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination.
Descriptors: Factor Analysis, Sample Size, Models, Sampling
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Straat, J. Hendrik; van der Ark, L. Andries; Sijtsma, Klaas – Educational and Psychological Measurement, 2014
An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…
Descriptors: Sampling, Test Items, Effect Size, Scaling
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Parrish, Danielle E.; Rubin, Allen – Research on Social Work Practice, 2011
This study utilized a replicated one-group pretest-posttest design with 3 month follow-up to evaluate the impact of a one-day continuing education training on the evidence-based practice (EBP) process with community practitioners (N = 69). Outcome measures assessed the level of workshop participants' familiarity with the EBP process, their…
Descriptors: Familiarity, Academic Achievement, Continuing Education, Workshops
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Kelley, Ken; Rausch, Joseph R. – Psychological Methods, 2011
Longitudinal studies are necessary to examine individual change over time, with group status often being an important variable in explaining some individual differences in change. Although sample size planning for longitudinal studies has focused on statistical power, recent calls for effect sizes and their corresponding confidence intervals…
Descriptors: Intervals, Sample Size, Effect Size, Longitudinal Studies
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Adedokun, Omolola A.; Childress, Amy L.; Burgess, Wilella D. – American Journal of Evaluation, 2011
A theory-driven approach to evaluation (TDE) emphasizes the development and empirical testing of conceptual models to understand the processes and mechanisms through which programs achieve their intended goals. However, most reported applications of TDE are limited to large-scale experimental/quasi-experimental program evaluation designs. Very few…
Descriptors: Feedback (Response), Program Evaluation, Structural Equation Models, Testing
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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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Konstantopoulos, Spyros – Journal of Experimental Education, 2010
Previous work on statistical power has discussed mainly single-level designs or 2-level balanced designs with random effects. Although balanced experiments are common, in practice balance cannot always be achieved. Work on class size is one example of unbalanced designs. This study provides methods for power analysis in 2-level unbalanced designs…
Descriptors: Class Size, Computers, Statistical Analysis, Experiments
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Marsh, Herbert W.; Bornmann, Lutz; Mutz, Rudiger; Daniel, Hans-Dieter; O'Mara, Alison – Review of Educational Research, 2009
Peer review is valued in higher education, but also widely criticized in terms of potential biases, particularly gender. We evaluate gender differences in peer reviews of grant applications, extending Bornmann, Mutz, and Daniel's meta-analyses that reported small gender differences in favor of men (d = 0.04), but a substantial heterogeneity in…
Descriptors: Effect Size, Gender Differences, Grants, Peer Evaluation
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Marascuilo, Leonard A.; And Others – Journal of Experimental Education, 1988
Large sample multivariate methods for estimating and comparing effect sizes across independent samples within a single study are presented. Procedures for pooling treatment effects are provided to allow determination of overall study effect sizes for treatments with similar effects prior to implementation of meta-analyses. (TJH)
Descriptors: Effect Size, Equations (Mathematics), Estimation (Mathematics), Meta Analysis
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