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Abdullah Mana Alfarwan – ProQuest LLC, 2024
This dissertation examined classification outcome differences among four popular individual supervised machine learning (ISML) models (logistic regression, decision tree, support vector machine, and multilayer perceptron) when predicting minor class membership within imbalanced datasets. The study context and the theoretical population sampled…
Descriptors: Regression (Statistics), Decision Making, Prediction, Sample Size
J. Vincent Nix; Yi-Chin Wu; Lan Misty Song; Joseph D. Levy – Research & Practice in Assessment, 2024
Traditionally, assessment professionals use analyses relying upon null hypothesis significance testing (NHST), but those tools have limitations when analyzing small samples or disaggregated data. This study used common NHST analytical techniques, compared their results, and then explored an alternative technique that perhaps allows for a more…
Descriptors: Sample Size, Statistical Significance, MOOCs, Geographic Location
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
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
Smith, Kendal N.; Lamb, Kristen N.; Henson, Robin K. – Gifted Child Quarterly, 2020
Multivariate analysis of variance (MANOVA) is a statistical method used to examine group differences on multiple outcomes. This article reports results of a review of MANOVA in gifted education journals between 2011 and 2017 (N = 56). Findings suggest a number of conceptual and procedural misunderstandings about the nature of MANOVA and its…
Descriptors: Multivariate Analysis, Academically Gifted, Gifted Education, Educational Research
Guo, Hongwen; Robin, Frederic; Dorans, Neil – Journal of Educational Measurement, 2017
The early detection of item drift is an important issue for frequently administered testing programs because items are reused over time. Unfortunately, operational data tend to be very sparse and do not lend themselves to frequent monitoring analyses, particularly for on-demand testing. Building on existing residual analyses, the authors propose…
Descriptors: Testing, Test Items, Identification, Sample Size
What Works Clearinghouse, 2020
The What Works Clearinghouse (WWC) is an initiative of the U.S. Department of Education's Institute of Education Sciences (IES), which was established under the Education Sciences Reform Act of 2002. It is an important part of IES's strategy to use rigorous and relevant research, evaluation, and statistics to improve the nation's education system.…
Descriptors: Educational Research, Evaluation Methods, Evidence, Statistical Significance
García-Pérez, Miguel A. – Educational and Psychological Measurement, 2017
Null hypothesis significance testing (NHST) has been the subject of debate for decades and alternative approaches to data analysis have been proposed. This article addresses this debate from the perspective of scientific inquiry and inference. Inference is an inverse problem and application of statistical methods cannot reveal whether effects…
Descriptors: Hypothesis Testing, Statistical Inference, Effect Size, Bayesian Statistics
Seastrom, Marilyn – Institute of Education Sciences, 2017
The Every Student Succeeds Act (ESSA) of 2015 (Public Law 114-95) requires each state to create a plan for its statewide accountability system. In particular, ESSA calls for state plans that include strategies for reporting education outcomes by grade for all students and for economically disadvantaged students, students from major racial and…
Descriptors: Accountability, Best Practices, Information Security, Sample Size
What Works Clearinghouse, 2017
The What Works Clearinghouse (WWC) systematic review process is the basis of many of its products, enabling the WWC to use consistent, objective, and transparent standards and procedures in its reviews, while also ensuring comprehensive coverage of the relevant literature. The WWC systematic review process consists of five steps: (1) Developing…
Descriptors: Educational Research, Evaluation Methods, Evidence, Statistical Significance
Thomas-Tate, Shurita; Daugherty, Timothy K. – Education, 2017
Employing an existing database of African American and biracial children entering metropolitan Detroit schools, we examined children of caregivers with and without reported stressful police contact. As anticipated, young children of caregivers with recent stressful police contact appear to suffer cognitive performance decrements on a nonverbal…
Descriptors: Minority Group Students, African American Students, Multiracial Persons, Urban Schools
Diliberti, Melissa; Jackson, Michael; Kemp, Jana – National Center for Education Statistics, 2017
This report presents findings on crime and violence in U.S. public schools, using data from the 2015-16 School Survey on Crime and Safety (SSOCS:2016). First administered in school year 1999-2000 and repeated in school years 2003-04, 2005-06, 2007-08, 2009-10, and 2015-16, SSOCS provides information on school crime-related topics from the…
Descriptors: Crime, Violence, Discipline, School Safety

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