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Stephanie Wermelinger; Marco Bleiker; Moritz M. Daum – Infant and Child Development, 2025
Children's fuzziness leads to increased variance in the data, data loss, and high dropout rates in developmental studies. This study investigated the importance of 20 factors on the person (child, caregiver, experimenter) and situation (task, method, time, and date) level for the data quality as indicated via the number of valid trials in 11…
Descriptors: Infants, Young Children, Research Problems, Factor Analysis
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Myunghwan Hwang; Soyeon Kim; Hyejin Kim; Joohee Han; Hee-Kyung Lee – English Teaching, 2024
This paper evaluates the use of Factor Analysis (FA) in English education research in Korea and suggests improvements in methodology. A detailed coding protocol was used to review 179 FA cases from 12 major English education journals (2014-2023). The review identified several key issues, including small sample sizes and lenient criteria for sample…
Descriptors: Factor Analysis, English (Second Language), Second Language Learning, Second Language Instruction
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Rai, Abha; Lee, Sunwoo; Jang, Jungwoo; Lee, Eunhye; Okech, David – Journal of Teaching in Social Work, 2022
The use of structural equation modeling (SEM) techniques in social work has increased over the last two decades. We therefore conducted a systematic review to understand the extent to which SEM is utilized in social work research, given that statistical training is now becoming a part of social work doctoral education. For our review, we utilized…
Descriptors: Structural Equation Models, Social Work, Social Science Research, Experiential Learning
Jennifer Shearman – Sage Research Methods Cases, 2022
This case study describes a Q methodology study which captured and analyzed the viewpoints of 45 UK teachers online. The teachers might liken their participation in the study to a "card sort" activity: their relative placement of statement cards revealed their opinions of mastery in mathematics. Factor analysis of the completed sorts…
Descriptors: Foreign Countries, Online Surveys, Research Methodology, Research Problems
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Kim, Yukyoum; Lee, J. Lucy – Measurement in Physical Education and Exercise Science, 2019
The purposes of this manuscript are to identify common statistical mistakes in sport management, and to provide scholars with suggestions on how to develop and improve the quality of quantitative research. We have reviewed articles published from 2001 to 2017 in the "Journal of Sport Management," "Sport Management Review,"…
Descriptors: Athletics, Research, Research Problems, Statistical Analysis
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Byon, Kevin K.; Zhang, James J. – Measurement in Physical Education and Exercise Science, 2019
Sport management research has evolved significantly despite its relatively short history as an academic discipline. Although the pace of scholarly progress has been impressive, the extent to which many research efforts have aided sport management in becoming a distinct academic discipline is, at times, questionable. A major challenge many scholars…
Descriptors: Athletics, Research, Statistical Analysis, Research Methodology
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Gagnon, Ryan J.; Stone, Garrett A.; Garst, Barry A. – Journal of Outdoor Recreation, Education, and Leadership, 2017
Critically examining common statistical approaches and their strengths and weaknesses is an important step in advancing recreation and leisure sciences. To continue this critical examination and to inform methodological decision making, this study compared three approaches to determine how alternative approaches may result in contradictory…
Descriptors: Recreation, Recreational Programs, Educational Research, Research Methodology
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Stapleton, Laura M.; McNeish, Daniel M.; Yang, Ji Seung – Educational Psychologist, 2016
Multilevel models are often used to evaluate hypotheses about relations among constructs when data are nested within clusters (Raudenbush & Bryk, 2002), although alternative approaches are available when analyzing nested data (Binder & Roberts, 2003; Sterba, 2009). The overarching goal of this article is to suggest when it is appropriate…
Descriptors: Hierarchical Linear Modeling, Data Analysis, Statistical Data, Multivariate Analysis
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Canivez, Gary L.; Kush, Joseph C. – Journal of Psychoeducational Assessment, 2013
Weiss, Keith, Zhu, and Chen (2013a) and Weiss, Keith, Zhu, and Chen (2013b), this issue, report examinations of the factor structure of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV), respectively; comparing Wechsler Hierarchical Model (W-HM) and…
Descriptors: Intelligence Tests, Factor Structure, Comparative Analysis, Arithmetic
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Martin, Andrew J.; Yu, Kai; Papworth, Brad; Ginns, Paul; Collie, Rebecca J. – Journal of Psychoeducational Assessment, 2015
This study explored motivation and engagement among North American (the United States and Canada; n = 1,540), U.K. (n = 1,558), Australian (n = 2,283), and Chinese (n = 3,753) secondary school students. Motivation and engagement were assessed via students' responses to the Motivation and Engagement Scale-High School (MES-HS). Confirmatory factor…
Descriptors: Foreign Countries, Motivation, Learner Engagement, Secondary School Students
Whitaker, Jean S. – 1997
The increased use of multiple regression analysis in research warrants closer examination of the coefficients produced in these analyses, especially ones which are often ignored, such as structure coefficients. Structure coefficients are bivariate correlation coefficients between a predictor variable and the synthetic variable. When predictor…
Descriptors: Correlation, Factor Analysis, Predictor Variables, Regression (Statistics)
Marsh, Herbert W. – 1988
During the last 15 years, there has been a steady increase in the popularity and sophistication of the confirmatory factor analysis approach to multitrait-multimethod (MTMM) data. However, important problems exist, the most serious being the ill-defined solutions that plague MTMM studies and the assumption that so-called method factors primarily…
Descriptors: Construct Validity, Factor Analysis, Multitrait Multimethod Techniques, Research Methodology
NORRELL, GWENDOLYN; ROKEACH, MILTON – 1966
THIS STUDY WAS CONCERNED WITH THE NATURE AND RELATIONSHIPS AMONG THE COGNITIVE FACTORS, ANALYSIS AND SYNTHESIS, AND THEIR PERSONALITY AND ACADEMIC CORRELATES. ENTERING FRESHMEN AT THE UNIVERSITY OF MICHIGAN WERE TESTED WITH A BATTERY OF NINE TESTS TO OBTAIN THE DATA REQUIRED FOR ANALYSIS. SUSPECTED CONTAMINATION OF THE TEST RESULTS DUE TO…
Descriptors: Cognitive Processes, Educational Research, Factor Analysis, Research Methodology
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Ruch, Libby O. – Sex Roles: A Journal of Research, 1984
Replicated Pedhazur and Tetenbaum's study that raised questions about the unidimensionality of the feminine and masculine subscales of Bem Sex Role Inventory (BSRI). Factor analysis and smallest space analysis indicated that subsets are not unidimensional. However, results of factor analysis but not smallest space analysis were consistent with…
Descriptors: Androgyny, Factor Analysis, Higher Education, Research Methodology
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Tuinman, J. Jaap; Blanton, B. Elgit. – Journal of Reading Behavior, 1970
Discusses articles by Richard Rystrom in the Winter and Spring 1970 issues of the Journal of Reading Behavior. Questions the validation procedures and statistical evidence behind the author's model of reading comprehension. Tables and bibliography. (RW)
Descriptors: Factor Analysis, Models, Reading Comprehension, Research Methodology
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