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Brunner, Martin; Keller, Lena; Stallasch, Sophie E.; Kretschmann, Julia; Hasl, Andrea; Preckel, Franzis; Lüdtke, Oliver; Hedges, Larry V. – Research Synthesis Methods, 2023
Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational…
Descriptors: Meta Analysis, Surveys, Research Design, Educational Research
Vaske, Jerry J. – Sagamore-Venture, 2019
Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…
Descriptors: Surveys, Theories, Hypothesis Testing, Effect Size
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Kaplan, David; Su, Dan – Journal of Educational and Behavioral Statistics, 2016
This article presents findings on the consequences of matrix sampling of context questionnaires for the generation of plausible values in large-scale assessments. Three studies are conducted. Study 1 uses data from PISA 2012 to examine several different forms of missing data imputation within the chained equations framework: predictive mean…
Descriptors: Sampling, Questionnaires, Measurement, International Assessment
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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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Zimmermann, Judith; Brodersen, Kay H.; Heinimann, Hans R.; Buhmann, Joachim M. – Journal of Educational Data Mining, 2015
The graduate admissions process is crucial for controlling the quality of higher education, yet, rules-of-thumb and domain-specific experiences often dominate evidence-based approaches. The goal of the present study is to dissect the predictive power of undergraduate performance indicators and their aggregates. We analyze 81 variables in 171…
Descriptors: Undergraduate Students, Graduate Students, Academic Achievement, Prediction
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Haber, Mason G.; Mazzotti, Valerie L.; Mustian, April L.; Rowe, Dawn A.; Bartholomew, Audrey L.; Test, David W.; Fowler, Catherine H. – Review of Educational Research, 2016
Students with disabilities experience poorer post-school outcomes compared with their peers without disabilities. Existing experimental literature on "what works" for improving these outcomes is rare; however, a rapidly growing body of research investigates correlational relationships between experiences in school and post-school…
Descriptors: Meta Analysis, Predictor Variables, Success, Postsecondary Education
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Agasisti, Tommaso – Education Economics, 2013
In this study, data envelopment analysis (DEA) is used to compute efficiency scores for a sample of Italian schools by employing OECD-PISA2006 data aggregated at school level. Efficiency has been defined as the ability to transform inputs (resources, student background, etc.) into outputs (student achievement). Different versions of the DEA models…
Descriptors: Foreign Countries, Secondary Schools, Efficiency, Competition
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Yagiz, Oktay; Aydin, Burcu; Akdemir, Ahmet Selçuk – Journal of Language and Linguistic Studies, 2016
This study reviews a selected sample of 274 research articles on ELT, published between 2005 and 2015 in Turkish contexts. In the study, 15 journals in ULAKBIM database and articles from national and international journals accessed according to convenience sampling method were surveyed and relevant articles were obtained. A content analysis was…
Descriptors: Journal Articles, Periodicals, Content Analysis, Research Design
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Osborne, Jason W. – Practical Assessment, Research & Evaluation, 2011
Large surveys often use probability sampling in order to obtain representative samples, and these data sets are valuable tools for researchers in all areas of science. Yet many researchers are not formally prepared to appropriately utilize these resources. Indeed, users of one popular dataset were generally found "not" to have modeled…
Descriptors: Best Practices, Sampling, Sample Size, Data Analysis
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Strizek, Gregory A.; Tourkin, Steve; Erberber, Ebru – National Center for Education Statistics, 2014
This technical report is designed to provide researchers with an overview of the design and implementation of the Teaching and Learning International Survey (TALIS) 2013. This information is meant to supplement that presented in OECD publications by describing those aspects of TALIS 2013 that are unique to the United States. Chapter 2 provides…
Descriptors: Learning, Instruction, Research Design, Program Implementation
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Hutchison, Dougal – Oxford Review of Education, 2008
There is a degree of instability in any measurement, so that if it is repeated, it is possible that a different result may be obtained. Such instability, generally described as "measurement error", may affect the conclusions drawn from an investigation, and methods exist for allowing it. It is less widely known that different disciplines, and…
Descriptors: Measurement Techniques, Data Analysis, Error of Measurement, Test Reliability
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Peng, Chao-Ying Joanne; Zhu, Jin – Educational and Psychological Measurement, 2008
For the past 25 years, methodological advances have been made in missing data treatment. Most published work has focused on missing data in dependent variables under various conditions. The present study seeks to fill the void by comparing two approaches for handling missing data in categorical covariates in logistic regression: the…
Descriptors: Regression (Statistics), Comparative Analysis, Evaluation Methods, Equations (Mathematics)
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Luyten, Hans; Tymms, Peter; Jones, Paul – School Effectiveness and School Improvement, 2009
The research findings presented in this paper illustrate how the "value added" of schooling can be assessed empirically using cross-sectional data. Application of the regression-discontinuity approach within a multilevel framework produces both an estimate of the absolute effect of 1 year schooling and an estimate of the variation across…
Descriptors: Academic Achievement, Longitudinal Studies, Sampling, Achievement Gains
Feng, Mingyu; Beck, Joseph E.; Heffernan, Neil T. – International Working Group on Educational Data Mining, 2009
A basic question of instructional interventions is how effective it is in promoting student learning. This paper presents a study to determine the relative efficacy of different instructional strategies by applying an educational data mining technique, learning decomposition. We use logistic regression to determine how much learning is caused by…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Sampling, Statistical Inference
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Ojeda, Mario Miguel; Sahai, Hardeo – International Journal of Mathematical Education in Science and Technology, 2002
Students in statistics service courses are frequently exposed to dogmatic approaches for evaluating the role of randomization in statistical designs, and inferential data analysis in experimental, observational and survey studies. In order to provide an overview for understanding the inference process, in this work some key statistical concepts in…
Descriptors: Probability, Data Analysis, Sampling, Statistical Inference
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