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McKay, Brad; Bacelar, Mariane F. B.; Carter, Michael J. – Journal of Motor Learning and Development, 2023
Recent metascience suggests that motor behavior research may be underpowered, on average. Researchers can perform a priori power analyses to ensure adequately powered studies. However, there are common pitfalls that can result in underestimating the required sample size for a given design and effect size of interest. Critical evaluation of power…
Descriptors: Statistical Analysis, Psychomotor Skills, Motor Development, Research Design
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Ting Dai; Yang Du; Jennifer Cromley; Tia Fechter; Frank Nelson – Journal of Experimental Education, 2024
Simple matrix sampling planned missing (SMS PD) design, introduce missing data patterns that lead to covariances between variables that are not jointly observed, and create difficulties for analyses other than mean and variance estimations. Based on prior research, we adopted a new multigroup confirmatory factor analysis (CFA) approach to handle…
Descriptors: Research Problems, Research Design, Data, Matrices
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Tipton, Elizabeth – American Journal of Evaluation, 2022
Practitioners and policymakers often want estimates of the effect of an intervention for their local community, e.g., region, state, county. In the ideal, these multiple population average treatment effect (ATE) estimates will be considered in the design of a single randomized trial. Methods for sample selection for generalizing the sample ATE to…
Descriptors: Sampling, Sample Size, Selection, Randomized Controlled Trials
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Shen, Zuchao; Kelcey, Benjamin – Journal of Experimental Education, 2022
Optimal design of multisite randomized trials leverages sampling costs to optimize sampling ratios and ultimately identify more efficient and powerful designs. Past implementations of the optimal design framework have assumed that costs of sampling units are equal across treatment conditions. In this study, we developed a more flexible optimal…
Descriptors: Randomized Controlled Trials, Sampling, Research Design, Statistical Analysis
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Shen, Zuchao; Kelcey, Benjamin – Journal of Research on Educational Effectiveness, 2022
Optimal sampling frameworks attempt to identify the most efficient sampling plans to achieve an adequate statistical power. Although such calculations are theoretical in nature, they are critical to the judicious and wise use of funding because they serve as important starting points that guide practical discussions around sampling tradeoffs and…
Descriptors: Sampling, Research Design, Randomized Controlled Trials, Statistical Analysis
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Bulus, Metin; Dong, Nianbo – Journal of Experimental Education, 2021
Sample size determination in multilevel randomized trials (MRTs) and multilevel regression discontinuity designs (MRDDs) can be complicated due to multilevel structure, monetary restrictions, differing marginal costs per treatment and control units, and range restrictions in sample size at one or more levels. These issues have sparked a set of…
Descriptors: Sampling, Research Methodology, Costs, Research Design
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Shen, Zuchao; Kelcey, Benjamin – Journal of Educational and Behavioral Statistics, 2020
Conventional optimal design frameworks consider a narrow range of sampling cost structures that thereby constrict their capacity to identify the most powerful and efficient designs. We relax several constraints of previous optimal design frameworks by allowing for variable sampling costs in cluster-randomized trials. The proposed framework…
Descriptors: Sampling, Research Design, Randomized Controlled Trials, Statistical Analysis
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Yao, Lili; Haberman, Shelby; McCaffrey, Daniel F.; Lockwood, J. R. – ETS Research Report Series, 2020
Minimum discriminant information adjustment (MDIA), an approach to weighting samples to conform to known population information, provides a generalization of raking and poststratification. In the case of simple random sampling with replacement with uniform sampling weights, large-sample properties are available for MDIA estimates of population…
Descriptors: Discriminant Analysis, Sampling, Sample Size, Scores
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Zorluoglu, Seraceddin Levent; Yalçinkaya Önder, Eylem; Timur, Betül; Timur, Serkan; Güvenç, Elif; Özergun, Ilgim; Özdemir, Muzaffer – Journal of Baltic Science Education, 2022
Science education focuses on the methods of thinking about and using process skills rather than memorizing scientific facts. 5E educational model aims to learn by discovering scientific knowledge and engaging students in learning environments. The aim of this study was to examine the articles in the field of education related to the 5E educational…
Descriptors: Science Process Skills, Models, Science Instruction, Teaching Methods
Public Policy Institute of California, 2021
The PPIC Statewide Survey was inaugurated in 1998 to provide a way for Californians to express their views on important public policy issues. The survey provides timely, relevant, nonpartisan information on Californians' political, social, and economic opinions. It seeks to inform and improve state policymaking, raise awareness, and encourage…
Descriptors: Research Methodology, Research Design, Sample Size, Data Collection
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Finch, W. Holmes; Finch, Maria Hernández – Journal of Experimental Education, 2018
Single subject (SS) designs are popular in educational and psychological research. There exist several statistical techniques designed to analyze such data and to address the question of whether an intervention has the desired impact. Recently, researchers have suggested that generalized additive models (GAMs) might be useful for modeling…
Descriptors: Educational Research, Longitudinal Studies, Simulation, Models
Makela, Susanna; Si, Yajuan; Gelman, Andrew – Grantee Submission, 2018
Cluster sampling is common in survey practice, and the corresponding inference has been predominantly design-based. We develop a Bayesian framework for cluster sampling and account for the design effect in the outcome modeling. We consider a two-stage cluster sampling design where the clusters are first selected with probability proportional to…
Descriptors: Bayesian Statistics, Statistical Inference, Sampling, Probability
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Madaus, Joseph W.; Dukes, Lyman L., III; Lalor, Adam R.; Aquino, Katherine; Faggella-Luby, Michael; Newman, Lynn A.; Papay, Clare; Petcu, Stefania; Scott, Sally; Wessel, Roger D. – Journal of Postsecondary Education and Disability, 2020
The body of research in the field of postsecondary education and disability is wide ranging and continues to evolve. Specifically, the literature corpus includes contributions from a range of professions and a considerable number of journals. This breadth of diversity in perspective presents significant advantages; however, it also presents…
Descriptors: Postsecondary Education, Educational Research, Guidelines, Students with Disabilities
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What Works Clearinghouse, 2018
Underlying all What Works Clearinghouse (WWC) products are WWC Study Review Guides, which are intended for use by WWC certified reviewers to assess studies against the WWC evidence standards. As part of an ongoing effort to increase transparency, promote collaboration, and encourage widespread use of the WWC standards, the Institute of Education…
Descriptors: Guides, Research Design, Research Methodology, Program Evaluation
Bulus, Metin – ProQuest LLC, 2017
In education, sample characteristics can be complex due to the nested structure of students, teachers, classrooms, schools, and districts. In the past, not many considerations were given to such complex sampling schemes in statistical power analysis. More recently in the past two decades, however, education scholars have developed tools to conduct…
Descriptors: Educational Research, Regression (Statistics), Research Design, Statistical Analysis
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