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Miratrix, Luke W.; Weiss, Michael J.; Henderson, Brit – Journal of Research on Educational Effectiveness, 2021
Researchers face many choices when conducting large-scale multisite individually randomized control trials. One of the most common quantities of interest in multisite RCTs is the overall average effect. Even this quantity is non-trivial to define and estimate. The researcher can target the average effect across individuals or sites. Furthermore,…
Descriptors: Computation, Randomized Controlled Trials, Error of Measurement, Regression (Statistics)
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Altintas, Ozge; Wallin, Gabriel – International Journal of Assessment Tools in Education, 2021
Educational assessment tests are designed to measure the same psychological constructs over extended periods. This feature is important considering that test results are often used for admittance to university programs. To ensure fair assessments, especially for those whose results weigh heavily in selection decisions, it is necessary to collect…
Descriptors: College Admission, College Entrance Examinations, Test Bias, Equated Scores
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Diaz, Emily; Brooks, Gordon; Johanson, George – International Journal of Assessment Tools in Education, 2021
This Monte Carlo study assessed Type I error in differential item functioning analyses using Lord's chi-square (LC), Likelihood Ratio Test (LRT), and Mantel-Haenszel (MH) procedure. Two research interests were investigated: item response theory (IRT) model specification in LC and the LRT and continuity correction in the MH procedure. This study…
Descriptors: Test Bias, Item Response Theory, Statistical Analysis, Comparative Analysis
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Feller, Avi; Stuart, Elizabeth A. – Journal of Research on Educational Effectiveness, 2021
Panel data methods, which include difference-in-differences and comparative interrupted time series, have become increasingly common in education policy research. The key idea is to use variation across time and space (e.g., school districts) to estimate the effects of policy or programmatic changes that happen in some localities but not others.…
Descriptors: COVID-19, Pandemics, Educational Policy, Statistical Analysis
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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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Thompson, Yutian T.; Song, Hairong; Shi, Dexin; Liu, Zhengkui – Educational and Psychological Measurement, 2021
Conventional approaches for selecting a reference indicator (RI) could lead to misleading results in testing for measurement invariance (MI). Several newer quantitative methods have been available for more rigorous RI selection. However, it is still unknown how well these methods perform in terms of correctly identifying a truly invariant item to…
Descriptors: Measurement, Statistical Analysis, Selection, Comparative Analysis
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Woodard, Victoria; Lee, Hollylynne – Journal of Statistics and Data Science Education, 2021
As the demand for skilled data scientists has grown, university level statistics and data science courses have become more rigorous in training students to understand and utilize the tools that their future careers will likely require. However, the mechanisms to assess students' use of these tools while they are learning to use them are not well…
Descriptors: College Students, Statistics Education, Statistical Analysis, Computation
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Brodersen, R. Marc; Gagnon, Douglas; Liu, Jing; Moss, Tony – Regional Educational Laboratory Central, 2021
This tool is intended to support state and local education agencies in developing a statistical model for estimating student postsecondary success at the school or district level. The tool guides education agency researchers, analysts, and decisionmakers through options to consider when developing their own model. The resulting model generates an…
Descriptors: Statistical Analysis, Models, Computation, Success
Feller, Avi; Stuart, Elizabeth A. – Grantee Submission, 2021
Panel data methods, which include difference-in-differences and comparative interrupted time series, have become increasingly com- mon in education policy research. The key idea is to use variation across time and space (e.g., school districts) to estimate the effects of policy or programmatic changes that happen in some localities but not others.…
Descriptors: COVID-19, Pandemics, Educational Policy, Statistical Analysis
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Traci Kutaka; Pavel Chernyavskiy; Carson Keeter; Julie Sarama; Douglas Clements – Society for Research on Educational Effectiveness, 2021
Background: Data on children's ability to answer assessment questions correctly paints an incomplete portrait of what they know and can do mathematically; yet, it remains a common basis for program evaluation. Indeed, pre-post-assessment correctness is necessary but insufficient evidence for making inferences about learning and program…
Descriptors: Kindergarten, Learning Trajectories, Learning Strategies, Thinking Skills
Angela N. Mabry – ProQuest LLC, 2024
With increased pressure for schools to demonstrate college and career readiness, it is crucial to explore the roles and activities of school counselors, the preservice training they receive, and how those college and career readiness concepts are integrated into their roles. The research questions were (1) What are the current roles and activities…
Descriptors: Middle Schools, High Schools, School Counselors, Career Readiness
Rebecca Burtenshaw; Merrilyn Goos – Mathematics Education Research Group of Australasia, 2024
This position paper examines the phenomenon of the McNamara Fallacy to analyse flawed conceptions of "success" in mathematics learning, normalised assessment structures and their implications for mathematics education. The established presence of the McNamara Fallacy and the ramifications of this statistical fallacy provide a foundation…
Descriptors: Criticism, Misconceptions, Mathematics Education, Success
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Stephanie D'Costa; Stephanie Grant; Tara Kulkarni; Adrianna Crossing; Miranda Zahn; Marie L. Tanaka – School Psychology International, 2024
School psychology has heavily relied on quantitative methodology to create and sustain our knowledge of best practices regarding academic, behavioral, and mental health outcomes for students. Nevertheless, underlying assumptions of the neutrality of quantitative data have obfuscated how school psychology research has perpetuated oppressive…
Descriptors: School Psychology, Criticism, Educational Research, Statistical Analysis
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Pooja Rana; Mithilesh Kumar Dubey; Lovi Raj Gupta; Amit Kumar Thakur – Interactive Learning Environments, 2024
In recent years, the system of student learning and academic emotions has been taken seriously to re-engineer the teaching-learning process at all levels of education. This research paper considers both aspects of assessing the translation of knowledge i.e. qualitative and quantitative. In the current scenario, quantitative and qualitative…
Descriptors: Educational Assessment, Outcomes of Education, Models, Evaluation Methods
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Seyda Ince Sezer; Mehmet Diyaddin Yasar – Science Insights Education Frontiers, 2024
The purpose of this research is to identify the situation through content analysis of scale development studies conducted by Turkish researchers in the field of preschool education. Thus, the overall trend of scale development research in preschool education was established. This research is a document analysis study. The documents studied are…
Descriptors: Foreign Countries, Preschool Education, Preschool Teachers, Measures (Individuals)
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