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No Child Left Behind Act 20014
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Lauren N. Layman; Brad A. Dufrene; Meleah M. Ackley; Caitlyn M. Weaver; Delaney E. Schneider; Zachary C. LaBrot; Crystal N. Taylor; Javid A. Rahaman; Kortlyn N. Tawney; Tearny Hart; D. Joe Olmi – Review Journal of Autism and Developmental Disorders, 2024
The purpose of the current study was to conduct a thorough review of the literature on the interview-informed synthesized contingency analysis (IISCA) developed by (Hanley et al., Journal of Applied Behavior Analysis 47:16-36, 2014)) and its subsequent treatment outcomes. A total of 39 articles were identified with 235 participants participating…
Descriptors: Behavior Problems, Interviews, Functional Behavioral Assessment, Outcomes of Treatment
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Sims, Sam; Anders, Jake; Inglis, Matthew; Lortie-Forgues, Hugues – Journal of Research on Educational Effectiveness, 2023
Randomized controlled trials have proliferated in education, in part because they provide an unbiased estimator for the causal impact of interventions. It is increasingly recognized that many such trials in education have low power to detect an effect if indeed there is one. However, it is less well known that low powered trials tend to…
Descriptors: Randomized Controlled Trials, Educational Research, Effect Size, Intervention
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Elliott, Mark; Buttery, Paula – Educational and Psychological Measurement, 2022
We investigate two non-iterative estimation procedures for Rasch models, the pair-wise estimation procedure (PAIR) and the Eigenvector method (EVM), and identify theoretical issues with EVM for rating scale model (RSM) threshold estimation. We develop a new procedure to resolve these issues--the conditional pairwise adjacent thresholds procedure…
Descriptors: Item Response Theory, Rating Scales, Computation, Simulation
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Henninger, Mirka; Debelak, Rudolf; Strobl, Carolin – Educational and Psychological Measurement, 2023
To detect differential item functioning (DIF), Rasch trees search for optimal split-points in covariates and identify subgroups of respondents in a data-driven way. To determine whether and in which covariate a split should be performed, Rasch trees use statistical significance tests. Consequently, Rasch trees are more likely to label small DIF…
Descriptors: Item Response Theory, Test Items, Effect Size, Statistical Significance
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Betsy Wolf – Society for Research on Educational Effectiveness, 2021
The What Works Clearinghouse (WWC) seeks to provide practitioners information about "what works in education." One challenge in understanding "what works" to practitioners is that effect sizes--the degree to which an intervention produces positive (or negative) outcomes--are not comparable across different interventions, in…
Descriptors: Effect Size, Outcome Measures, Intervention, Educational Research
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Chan, Wendy; Hedges, Larry V.; Hedberg, E. C. – Journal of Experimental Education, 2022
Many experimental designs in educational and behavioral research involve at least one level of clustering. Clustering affects the precision of estimators and its impact on statistics in cross-sectional studies is well known. Clustering also occurs in longitudinal designs where students that are initially grouped may be regrouped in the following…
Descriptors: Educational Research, Multivariate Analysis, Longitudinal Studies, Effect Size
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Rubio-Aparicio, María; López-López, José Antonio; Viechtbauer, Wolfgang; Marín-Martínez, Fulgencio; Botella, Juan; Sánchez-Meca, Julio – Journal of Experimental Education, 2020
Mixed-effects models can be used to examine the association between a categorical moderator and the magnitude of the effect size. Two approaches are available to estimate the residual between-studies variance, t[superscript 2][subscript res] --namely, separate estimation within each category of the moderator versus pooled estimation across all…
Descriptors: Meta Analysis, Effect Size, Computation, Classification
Deng, Lifang; Yuan, Ke-Hai – Grantee Submission, 2022
Structural equation modeling (SEM) has been deemed as a proper method when variables contain measurement errors. In contrast, path analysis with composite-scores is preferred for prediction and diagnosis of individuals. While path analysis with composite-scores has been criticized for yielding biased parameter estimates, recent literature pointed…
Descriptors: Structural Equation Models, Path Analysis, Weighted Scores, Error of Measurement
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Leckie, George; Prior, Lucy – School Effectiveness and School Improvement, 2022
School accountability systems increasingly hold schools to account for their performances using value-added models purporting to measure the effects of schools on student learning. The most common approach is to fit a linear regression of student current achievement on student prior achievement, where the school effects are the school means of the…
Descriptors: Value Added Models, Accountability, Secondary Schools, Educational Practices
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Karadavut, Tugba – Applied Measurement in Education, 2021
Mixture IRT models address the heterogeneity in a population by extracting latent classes and allowing item parameters to vary between latent classes. Once the latent classes are extracted, they need to be further examined to be characterized. Some approaches have been adopted in the literature for this purpose. These approaches examine either the…
Descriptors: Item Response Theory, Models, Test Items, Maximum Likelihood Statistics
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Wolf, Rebecca – What Works Clearinghouse, 2021
The What Works Clearinghouse (WWC) seeks to provide practitioners information about "what works in education." One challenge in understanding "what works" is that effect sizes may not be comparable across studies, which limits the ability to compare the relative effectiveness of multiple interventions. One factor that…
Descriptors: Effect Size, Outcome Measures, Educational Research, Differences
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Niu, Lian – Educational Review, 2020
This study reviews the international literature of empirical educational research to examine the application of logistic regression. The aim is to examine common practices of the report and interpretation of logistic regression results, and to discuss the implications for educational research. A review of 130 studies suggests that: (a) the…
Descriptors: Regression (Statistics), Educational Research, Statistical Significance, Predictor Variables
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Simsek, Ahmet Salih – International Journal of Assessment Tools in Education, 2023
Likert-type item is the most popular response format for collecting data in social, educational, and psychological studies through scales or questionnaires. However, there is no consensus on whether parametric or non-parametric tests should be preferred when analyzing Likert-type data. This study examined the statistical power of parametric and…
Descriptors: Error of Measurement, Likert Scales, Nonparametric Statistics, Statistical Analysis
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Jane E. Miller – Numeracy, 2023
Students often believe that statistical significance is the only determinant of whether a quantitative result is "important." In this paper, I review traditional null hypothesis statistical testing to identify what questions inferential statistics can and cannot answer, including statistical significance, effect size and direction,…
Descriptors: Statistical Significance, Holistic Approach, Statistical Inference, Effect Size
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Oleson, Jacob J.; Brown, Grant D.; McCreery, Ryan – Journal of Speech, Language, and Hearing Research, 2019
Purpose: Clinicians depend on the accuracy of research in the speech, language, and hearing sciences to improve assessment and treatment of patients with communication disorders. Although this work has contributed to great advances in clinical care, common statistical misconceptions remain, which deserve closer inspection in the field. Challenges…
Descriptors: Statistics, Speech Language Pathology, Research, Statistical Analysis
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