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Drechsler, Jörg – Journal of Educational and Behavioral Statistics, 2015
Multiple imputation is widely accepted as the method of choice to address item-nonresponse in surveys. However, research on imputation strategies for the hierarchical structures that are typically found in the data in educational contexts is still limited. While a multilevel imputation model should be preferred from a theoretical point of view if…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Educational Research, Statistical Bias
Dani, Anita; Nasser, Ramzi – Turkish Online Journal of Educational Technology - TOJET, 2016
The purpose of this paper is to determine potential identifiers of students' academic success in foundation mathematics course from the data logs of the intelligent tutor Assessment for Learning using Knowledge Spaces (ALEKS). A cross-sectional study design was used. A sample of 152 records, which accounts to approximately 60% of the population,…
Descriptors: Postsecondary Education, Mathematics Education, Intelligent Tutoring Systems, Technology Uses in Education
French, Brian F.; Finch, W. Holmes – Educational and Psychological Measurement, 2013
Multilevel data structures are ubiquitous in the assessment of differential item functioning (DIF), particularly in large-scale testing programs. There are a handful of DIF procures for researchers to select from that appropriately account for multilevel data structures. However, little, if any, work has been completed to extend a popular DIF…
Descriptors: Test Bias, Statistical Analysis, Comparative Analysis, Correlation
Rhoads, Christopher – Journal of Research on Educational Effectiveness, 2016
Experimental evaluations that involve the educational system usually involve a hierarchical structure (students are nested within classrooms that are nested within schools, etc.). Concerns about contamination, where research subjects receive certain features of an intervention intended for subjects in a different experimental group, have often led…
Descriptors: Educational Experiments, Error of Measurement, Research Design, Statistical Analysis
Westine, Carl D. – Society for Research on Educational Effectiveness, 2015
A cluster-randomized trial (CRT) relies on random assignment of intact clusters to treatment conditions, such as classrooms or schools (Raudenbush & Bryk, 2002). One specific type of CRT, a multi-site CRT (MSCRT), is commonly employed in educational research and evaluation studies (Spybrook & Raudenbush, 2009; Spybrook, 2014; Bloom,…
Descriptors: Correlation, Randomized Controlled Trials, Science Achievement, Cluster Grouping
Lai, Mark H. C.; Kwok, Oi-man – Journal of Experimental Education, 2015
Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…
Descriptors: Educational Research, Research Design, Cluster Grouping, Statistical Data
Amsale, Frew; Bekele, Mitiku; Tafesse, Mebratu – Online Submission, 2016
The purpose of this study was to assess the extent to which educational leaders in the western cluster public universities of Ethiopia are ethical. Ethical leadership variables such as fairness, equity, multicultural competence, modeling ethical behaviors and altruism are considered in describing the ethical behaviors of the leaders. Descriptive…
Descriptors: Foreign Countries, Public Colleges, Ethics, Cluster Grouping
Ellis, Robert A. – Active Learning in Higher Education, 2016
There is variation in the university student experience of learning. Prior research has shown that factors that shape this include student characteristics, the learning context, student perceptions of that context and approaches to learning and their learning outcomes. In blended contexts, there is a need to identify variables which can explain…
Descriptors: Student Experience, Educational Environment, Inquiry, Higher Education
Karagiannakis, Giannis N.; Baccaglini-Frank, Anna E.; Roussos, Petros – Australian Journal of Learning Difficulties, 2016
Through a review of the literature on mathematical learning disabilities (MLD) and low achievement in mathematics (LA) we have proposed a model classifying mathematical skills involved in learning mathematics into four domains (Core number, Memory, Reasoning, and Visual-spatial). In this paper we present a new experimental computer-based battery…
Descriptors: Mathematics Skills, Mathematical Aptitude, Skill Analysis, Learning Disabilities
Van den Berghe, Lynn; Cardon, Greet; Aelterman, Nathalie; Tallir, Isabel Barbara; Vansteenkiste, Maarten; Haerens, Leen – Journal of Teaching in Physical Education, 2013
Burnout in teachers is related to different maladaptive outcomes. This study aimed at exploring the relationship between emotional exhaustion and motivation to teach in 93 physical education teachers. Results showed that teachers report more emotional exhaustion when they are less autonomously motivated, while the opposite relationship was found…
Descriptors: Foreign Countries, Physical Education, Physical Education Teachers, Teacher Motivation
De Luca, Barbara M.; Hinshaw, Steven A. – Educational Considerations, 2013
The purpose of this research was to investigate the role of school district expenditures in predicting student achievement in Ohio for the school year 2009-2010. Building upon the concept of the "65 percent solution," the research questions that guided this study were: (1) What percentage of Ohio's school district's operating budgets…
Descriptors: Academic Achievement, Predictor Variables, Predictive Validity, Expenditures
Dong, Nianbo; Lipsey, Mark – Society for Research on Educational Effectiveness, 2010
This study uses simulation techniques to examine the statistical power of the group- randomized design and the matched-pair (MP) randomized block design under various parameter combinations. Both nearest neighbor matching and random matching are used for the MP design. The power of each design for any parameter combination was calculated from…
Descriptors: Simulation, Statistical Analysis, Cluster Grouping, Mathematical Models
Konstantopoulos, Spyros – Evaluation Review, 2009
In experimental designs with nested structures, entire groups (such as schools) are often assigned to treatment conditions. Key aspects of the design in these cluster-randomized experiments involve knowledge of the intraclass correlation structure, the effect size, and the sample sizes necessary to achieve adequate power to detect the treatment…
Descriptors: Statistical Analysis, Cluster Grouping, Research Design, Sample Size
Hendrix, Dean – College & Research Libraries, 2010
This study analyzed 2005-2006 Web of Science bibliometric data from institutions belonging to the Association of Research Libraries (ARL) and corresponding ARL statistics to find any associations between indicators from the two data sets. Principal components analysis on 36 variables from 103 universities revealed obvious associations between…
Descriptors: Bibliometrics, Correlation, Research Libraries, Library Associations
Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2007
A common mistake in analysis of cluster randomized trials is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This typically leads to an overstatement of the precision of results and anticonservative conclusions about precision and statistical significance of treatment effects. This…
Descriptors: Statistical Significance, Computation, Cluster Grouping, Statistics
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