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Nese, Joseph F. T.; Stevens, Joseph J.; Schulte, Ann C.; Tindal, Gerald; Elliott, Stephen N. – Journal of Special Education, 2017
Our purpose was to examine different approaches to modeling the time-varying nature of exceptionality classification. Using longitudinal data from one state's mathematics achievement test for 28,829 students in Grades 3 to 8, we describe the reclassification rate within special education and between general and special education, and compare four…
Descriptors: Classification, Achievement Gains, Special Needs Students, Mathematics Achievement
Gubbels, Joyce; Segers, Eliane; Keuning, Jos; Verhoeven, Ludo – Gifted Child Quarterly, 2016
The theory of triarchic intelligence posits that, in addition to the widely acknowledged analytical reasoning abilities, creative and practical abilities should be included in the assessments of intellectual capacities and identification of gifted students. To find support for such an approach, the present study examined the psychometric…
Descriptors: Academically Gifted, Elementary School Students, Correlation, Factor Analysis
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Wu, Wei; West, Stephen G. – Multivariate Behavioral Research, 2010
This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…
Descriptors: Goodness of Fit, Computation, Statistical Analysis, Structural Equation Models
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Skinner, Ellen; Pitzer, Jennifer; Steele, Joel – Educational and Psychological Measurement, 2013
A study was designed to examine a multidimensional measure of children's coping in the academic domain as part of a larger model of motivational resilience. Using items tapping multiple ways of dealing with academic problems, including five adaptive ways (strategizing, help-seeking, comfort-seeking, self-encouragement, and commitment) and six…
Descriptors: Coping, Resilience (Psychology), Student Motivation, Student Adjustment
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Leite, Walter L.; Sandbach, Robert; Jin, Rong; MacInnes, Jann W.; Jackman, M. Grace-Anne – Structural Equation Modeling: A Multidisciplinary Journal, 2012
Because random assignment is not possible in observational studies, estimates of treatment effects might be biased due to selection on observable and unobservable variables. To strengthen causal inference in longitudinal observational studies of multiple treatments, we present 4 latent growth models for propensity score matched groups, and…
Descriptors: Structural Equation Models, Probability, Computation, Observation