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Showing 1 to 15 of 18 results Save | Export
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Fangxing Bai; Ben Kelcey; Yanli Xie; Kyle Cox – Journal of Experimental Education, 2025
Prior research has suggested that clustered regression discontinuity designs are a formidable alternative to cluster randomized designs because they provide targeted treatment assignment while maintaining a high-quality basis for inferences on local treatment effects. However, methods for the design and analysis of clustered regression…
Descriptors: Regression (Statistics), Statistical Analysis, Research Design, Educational Research
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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Kern, Holger L.; Stuart, Elizabeth A.; Hill, Jennifer; Green, Donald P. – Journal of Research on Educational Effectiveness, 2016
Randomized experiments are considered the gold standard for causal inference because they can provide unbiased estimates of treatment effects for the experimental participants. However, researchers and policymakers are often interested in using a specific experiment to inform decisions about other target populations. In education research,…
Descriptors: Educational Research, Generalization, Sampling, Participant Characteristics
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Pustejovsky, James Eric – AERA Online Paper Repository, 2017
Methods for meta-analyzing single-case designs (SCDs) are needed in order to inform evidence based practice in special education and to draw broader and more defensible generalizations in areas where SCDs comprise a large part of the research base. The most widely used outcomes in single-case research are measures of behavior collected using…
Descriptors: Effect Size, Research Design, Meta Analysis, Observation
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What Works Clearinghouse, 2015
The What Works Clearinghouse (WWC) Standards Briefs explain the rules the WWC uses to evaluate the quality of studies for practitioners, researchers, and policymakers. Attrition (loss of sample) occurs when individuals initially included in a study are not included in the final study analysis. Attrition is a common issue in education research and…
Descriptors: Program Effectiveness, Educational Research, Attrition (Research Studies), Student Attrition
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Ilic, Ulas; Haseski, Halil Ibrahim; Tugtekin, Ufuk – Contemporary Educational Technology, 2018
The current study aimed to review studies on computational thinking (CT) indexed in Web of Science (WOS) and ERIC databases. A thorough search in electronic databases revealed 96 studies on computational thinking which were published between 2006 and 2016. Studies were exposed to a quantitative content analysis through using an article control…
Descriptors: Trend Analysis, Educational Trends, Periodicals, Databases
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Finch, W. Holmes – Journal of Experimental Education, 2016
Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…
Descriptors: Multivariate Analysis, Educational Research, Error of Measurement, Research Problems
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Lai, Mark H. C.; Kwok, Oi-Man – Journal of Educational and Behavioral Statistics, 2014
Multilevel modeling techniques are becoming more popular in handling data with multilevel structure in educational and behavioral research. Recently, researchers have paid more attention to cross-classified data structure that naturally arises in educational settings. However, unlike traditional single-level research, methodological studies about…
Descriptors: Hierarchical Linear Modeling, Differences, Effect Size, Computation
Stovall, Holly – ProQuest LLC, 2012
Over the past decade educational research has been stimulated by new legislation such as the No Child Left Behind Act. Increasing emphasis is being placed on accurately quantifying the success of treatment programs through student achievement scores, so precise estimation is vital for establishing the efficacy of new methodology. Ranked set…
Descriptors: Sampling, Educational Research, Hierarchical Linear Modeling, Nonparametric Statistics
Deke, John; Dragoset, Lisa – Mathematica Policy Research, Inc., 2012
The regression discontinuity design (RDD) has the potential to yield findings with causal validity approaching that of the randomized controlled trial (RCT). However, Schochet (2008a) estimated that, on average, an RDD study of an education intervention would need to include three to four times as many schools or students as an RCT to produce…
Descriptors: Research Design, Elementary Secondary Education, Regression (Statistics), Educational Research
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Schochet, Peter Z.; Puma, Mike; Deke, John – National Center for Education Evaluation and Regional Assistance, 2014
This report summarizes the complex research literature on quantitative methods for assessing how impacts of educational interventions on instructional practices and student learning differ across students, educators, and schools. It also provides technical guidance about the use and interpretation of these methods. The research topics addressed…
Descriptors: Statistical Analysis, Evaluation Methods, Educational Research, Intervention
Reardon, Sean F. – Society for Research on Educational Effectiveness, 2010
Instrumental variable estimators hold the promise of enabling researchers to estimate the effects of educational treatments that are not (or cannot be) randomly assigned but that may be affected by randomly assigned interventions. Examples of the use of instrumental variables in such cases are increasingly common in educational and social science…
Descriptors: Social Science Research, Least Squares Statistics, Computation, Correlation
Brese, Falk, Ed. – International Association for the Evaluation of Educational Achievement, 2012
The Teacher Education Study in Mathematics or TEDS-M is a study conducted under the aegis of the International Association for the Evaluation of Educational Achievement (IEA). The lead research center for the study is the International Study Center at Michigan State University (ISC/MSU). The ISC/MSU worked from 2006 to 2011 with the International…
Descriptors: Preservice Teacher Education, Elementary School Teachers, Secondary School Teachers, Mathematics Teachers
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Zhu, Pei; Jacob, Robin; Bloom, Howard; Xu, Zeyu – Educational Evaluation and Policy Analysis, 2012
This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools--which comprise three levels of clustering (students in classrooms in schools)--to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises…
Descriptors: Educational Research, Educational Researchers, Research Methodology, Multivariate Analysis
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Olsen, Robert B.; Unlu, Fatih; Price, Cristofer; Jaciw, Andrew P. – National Center for Education Evaluation and Regional Assistance, 2011
This report examines the differences in impact estimates and standard errors that arise when these are derived using state achievement tests only (as pre-tests and post-tests), study-administered tests only, or some combination of state- and study-administered tests. State tests may yield different evaluation results relative to a test that is…
Descriptors: Achievement Tests, Standardized Tests, State Standards, Reading Achievement
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