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Finch, W. Holmes – Journal of Experimental Education, 2022
Multivariate analysis of variance (MANOVA) is widely used to test the null hypothesis of equal multivariate means across 2 or more groups. MANOVA rests upon an assumption that error terms are independent of one another, which can be violated if individuals are clustered or nested within groups, such as schools. Ignoring such nesting can result in…
Descriptors: Multivariate Analysis, Hypothesis Testing, Structural Equation Models, Hierarchical Linear Modeling
McNeish, Daniel – Journal of Experimental Education, 2018
Small samples are common in growth models due to financial and logistical difficulties of following people longitudinally. For similar reasons, longitudinal studies often contain missing data. Though full information maximum likelihood (FIML) is popular to accommodate missing data, the limited number of studies in this area have found that FIML…
Descriptors: Growth Models, Sampling, Sample Size, Hierarchical Linear Modeling
Heddy, Benjamin C.; Danielson, Robert W.; Sinatra, Gale M.; Graham, Jesse – Journal of Experimental Education, 2017
The purpose of this study was to explore whether conceptual change predicted emotional and attitudinal change while learning about genetically modified foods (GMFs). Participants were 322 college students; half read a refutation text designed to shift conceptual knowledge, emotions, and attitudes, while the other half served as a control group.…
Descriptors: Genetics, Food, Attitude Change, Science Education
Chen, Yi-Hsin; Thompson, Marilyn S.; Kromrey, Jeffrey D.; Chang, George H. – Journal of Experimental Education, 2011
In this article, the authors investigated the relations of students' perceptions of teachers' oral feedback with teacher expectancies and student self-concept. A sample of 1,598 Taiwanese children in Grades 3 to 6 completed measures of student perceptions of teacher oral feedback and school self-concept. Homeroom teachers identified students for…
Descriptors: Feedback (Response), Student Attitudes, Structural Equation Models, Discriminant Analysis