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Peer reviewedHayduk, Leslie; Cummings, Greta; Stratkotter, Rainer; Nimmo, Melanie; Grygoryev, Kostyantyn; Dosman, Donna; Gillespie, Michael; Pazderka-Robinson, Hannah; Boadu, Kwame – Structural Equation Modeling, 2003
Provides an introduction to the structural equation modeling concepts developed by J. Pearl, discussing the concept he calls "d-separation." Explains how d-separation connects to control variables, partial correlations, causal structuring, and even a potential mistake in regression. (SLD)
Descriptors: Causal Models, Correlation, Structural Equation Models, Theories
Gignac, G.E. – Intelligence, 2005
Using a semi-partial correlation approach, Gignac, Stough, and Loukomitis [Gignac, G. E., Stough, C., & Loukomitis, S. (2004). Openness, intelligence, and self-report intelligence. Intelligence, 32, 133-143] examined the relationship between Openness and 'g' and residualized scores from Vocabulary and Information as estimates of crystallized…
Descriptors: Figurative Language, Intelligence, Structural Equation Models, Models
Willse, John T.; Goodman, Joshua T.; Allen, Nancy; Klaric, John – Applied Measurement in Education, 2008
The current research demonstrates the effectiveness of using structural equation modeling (SEM) for the investigation of subgroup differences with sparse data designs where not every student takes every item. Simulations were conducted that reflected missing data structures like those encountered in large survey assessment programs (e.g., National…
Descriptors: Structural Equation Models, Simulation, Item Response Theory, Factor Analysis
Enders, Craig K.; Tofighi, Davood – Structural Equation Modeling: A Multidisciplinary Journal, 2008
The purpose of this study was to examine the impact of misspecifying a growth mixture model (GMM) by assuming that Level-1 residual variances are constant across classes, when they do, in fact, vary in each subpopulation. Misspecification produced bias in the within-class growth trajectories and variance components, and estimates were…
Descriptors: Structural Equation Models, Computation, Monte Carlo Methods, Evaluation Methods
Betts, Lucy R.; Elder, Tracey J.; Hartley, James; Blurton, Anthony – Educational Studies, 2008
Recent initiatives to enhance retention and widen participation ensure it is crucial to understand the factors that predict students' performance during their undergraduate degree. The present research used Structural Equation Modeling (SEM) to test three separate models that examined the extent to which British Psychology students' A-level entry…
Descriptors: Structural Equation Models, Academic Achievement, Psychology, Higher Education
Markovits, Yannis; Ullrich, Johannes; van Dick, Rolf; Davis, Ann J. – Journal of Vocational Behavior, 2008
We use regulatory focus theory to derive specific predictions regarding the differential relationships between regulatory focus and commitment. We estimated a structural equation model using a sample of 520 private and public sector employees and found in line with our hypotheses that (a) promotion focus related more strongly to affective…
Descriptors: Prevention, Public Sector, Human Resources, Structural Equation Models
McDowell, Jennifer E.; Dyckman, Kara A.; Austin, Benjamin P.; Clementz, Brett A. – Brain and Cognition, 2008
This review provides a summary of the contributions made by human functional neuroimaging studies to the understanding of neural correlates of saccadic control. The generation of simple visually guided saccades (redirections of gaze to a visual stimulus or pro-saccades) and more complex volitional saccades require similar basic neural circuitry…
Descriptors: Structural Equation Models, Short Term Memory, Brain, Cognitive Processes
Hagemann, Dirk; Meyerhoff, David – Structural Equation Modeling: A Multidisciplinary Journal, 2008
The latent state-trait (LST) theory is an extension of the classical test theory that allows one to decompose a test score into a true trait, a true state residual, and an error component. For practical applications, the variances of these latent variables may be estimated with standard methods of structural equation modeling (SEM). These…
Descriptors: Structural Equation Models, Test Theory, Reliability, Sample Size
Leong, Che Kan; Tse, Shek Kam; Loh, Ka Yee; Hau, Kit Tai – Journal of Educational Psychology, 2008
The present study examined the role of verbal working memory (memory span, tongue twister), 2-character Chinese pseudoword reading, rapid automatized naming (letters, numbers), and phonological segmentation (deletion of rimes and onsets) in inferential text comprehension in Chinese in 518 Chinese children in Hong Kong in Grades 3 to 5. It was…
Descriptors: Reading Comprehension, Structural Equation Models, Memory, Foreign Countries
Takahira, Mieko; Ando, Reiko; Sakamoto, Akira – Computers in the Schools, 2008
This study focused on whether Internet use improves skills for practical use of information, which is termed information literacy in Japan. Data from Japanese elementary school children (n = 702) were analyzed in a two-wave panel study in order to estimate the causal relationship between Internet use and information literacy. Structural equation…
Descriptors: Elementary School Students, Structural Equation Models, Foreign Countries, Information Literacy
Nelson, Joretta – ProQuest LLC, 2010
With retention and persistence-to-graduation rates showing little improvement in previous decades, institutions of higher education continue to seek ways to encourage students to take responsibility for their own learning in order to achieve. The primary purpose of this study was to examine the roles and relationships of selected psychological and…
Descriptors: Higher Education, Ethnicity, Grade Point Average, Graduation Rate
Mooshegian, Stephanie E. – ProQuest LLC, 2010
The current study merges theory and research in higher education and organizational psychology in order to investigate student retention in adult learners. Factors that are associated with student retention were examined and points of intervention are recommended. Specifically, this study focuses on the role of campus environment, classroom…
Descriptors: Feedback (Response), Intervention, Structural Equation Models, Methods
Brown, Sharon A. – ProQuest LLC, 2010
School reform policies have failed to produce sustained positive changes in education practice. Theories of school change provide structure to reform policy. Program evaluations focus on implementation and outcomes but seldom test the theoretical assumptions of the initiative. This study tested theory, specifically the influence of…
Descriptors: Structural Equation Models, Ownership, Economic Status, Literacy
Goddard, Yvonne L.; Miller, Robert; Larsen, Ross; Goddard, Roger; Madsen, Jean; Schroeder, Patricia – Online Submission, 2010
The purpose of this paper was to test the relationship between principal leadership and teacher collaboration around instructional improvement to determine whether these measures were statistically related and whether, together, they were associated with academic achievement in elementary schools. Data were obtained from 1,600 teachers in 96…
Descriptors: Structural Equation Models, Instructional Improvement, Academic Achievement, Teacher Collaboration
Ning, Hoi Kwan; Downing, Kevin – Studies in Higher Education, 2010
This study investigated the effects of supplemental instruction, a peer-assisted learning approach, on students, learning competence and academic performance. The supplemental instruction intervention facilitated by senior students focused on developing students' use of study skills and enhancing their motivation and academic performance. Pre- and…
Descriptors: Educational Strategies, Undergraduate Students, Intervention, Structural Equation Models

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