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Gyeongcheol Cho; Heungsun Hwang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Generalized structured component analysis (GSCA) is a multivariate method for specifying and examining interrelationships between observed variables and components. Despite its data-analytic flexibility honed over the decade, GSCA always defines every component as a linear function of observed variables, which can be less optimal when observed…
Descriptors: Prediction, Methods, Networks, Simulation
Kjorte Harra; David Kaplan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The present work focuses on the performance of two types of shrinkage priors--the horseshoe prior and the recently developed regularized horseshoe prior--in the context of inducing sparsity in path analysis and growth curve models. Prior research has shown that these horseshoe priors induce sparsity by at least as much as the "gold…
Descriptors: Structural Equation Models, Bayesian Statistics, Regression (Statistics), Statistical Inference
Ke-Hai Yuan; Zhiyong Zhang – Grantee Submission, 2022
Structural equation modeling (SEM) is a widely used technique for studies involving latent constructs. While covariance-based SEM (CB-SEM) permits estimating the regression relationship among latent constructs, the parameters governing this relationship do not apply to that among the scored values of the constructs, which are needed for…
Descriptors: Psychometrics, Structural Equation Models, Scores, Least Squares Statistics
Hilley, Chanler D.; O'Rourke, Holly P. – International Journal of Behavioral Development, 2022
Researchers in behavioral sciences are often interested in longitudinal behavior change outcomes and the mechanisms that influence changes in these outcomes over time. The statistical models that are typically implemented to address these research questions do not allow for investigation of mechanisms of dynamic change over time. However, latent…
Descriptors: Behavioral Science Research, Research Methodology, Longitudinal Studies, Behavior Change
Edelsbrunner, Peter; Schneider, Michael – Frontline Learning Research, 2013
Musso et al. (2013) predict students' academic achievement with high accuracy one year in advance from cognitive and demographic variables, using artificial neural networks (ANNs). They conclude that ANNs have high potential for theoretical and practical improvements in learning sciences. ANNs are powerful statistical modelling tools but they can…
Descriptors: Prediction, Statistical Analysis, Structural Equation Models, Academic Achievement
Wang, Qi; Fink, Edward L.; Cai, Deborah A. – Human Communication Research, 2012
Avoidance is proposed to be a goal-directed behavior rather than a behavior that reflects passivity or inaction. To evaluate this proposition, a typology of conflict goals and a typology of conflict avoidance strategies are created, and the relationship between nonavoidance strategies and the elements of these 2 typologies are evaluated within a…
Descriptors: Structural Equation Models, Conflict, Classification, Evaluation
Williford, Anne; Boulton, Aaron; Noland, Brian; Little, Todd D.; Karna, Antti; Salmivalli, Christina – Journal of Abnormal Child Psychology, 2012
The present study investigated the effects of the KiVa antibullying program on students' anxiety, depression, and perception of peers in Grades 4-6. Furthermore, it was investigated whether reductions in peer-reported victimization predicted changes in these outcome variables. The study participants included 7,741 students from 78 schools who were…
Descriptors: Bullying, Structural Equation Models, Victims, Depression (Psychology)
Fuchs, Bruce A.; Miller, Jon D. – Peabody Journal of Education, 2012
Physicians and other health professionals are an important part of the national scientific and technical workforce, and it is important to understand the factors that attract (or fail to attract) young adults into these fields. Using data from the 20-year record of the Longitudinal Study of American Youth (LSAY) and working within a social…
Descriptors: Socialization, Health Occupations, Career Choice, Physicians
Pearson, Willie, Jr.; Miller, Jon D. – Peabody Journal of Education, 2012
Utilizing data from the 20-year record of the Longitudinal Study of American Youth (LSAY), this analysis uses a set of variables to predict employment in engineering for a national sample of adults aged 34 to 37. The LSAY is one of the longest longitudinal studies of the impact of secondary education and postsecondary education conducted in the…
Descriptors: Education Work Relationship, Engineering, Longitudinal Studies, Calculus
Michel, Jesse S.; Clark, Malissa A.; Jaramillo, David – Journal of Vocational Behavior, 2011
The present meta-analysis examines the relationships between the Five Factor Model (FFM) of personality and negative and positive forms of work-nonwork spillover (e.g., work-family conflict and facilitation). Results, based on aggregated correlations drawn from 66 studies and 72 independent samples (Total N = 28,127), reveal that the FFM is…
Descriptors: Personality Traits, Structural Equation Models, Personality, Personality Measures
Romer, Daniel; Betancourt, Laura M.; Brodsky, Nancy L.; Giannetta, Joan M.; Yang, Wei; Hurt, Hallam – Developmental Science, 2011
Studies of brain development suggest that the increase in risk taking observed during adolescence may be due to insufficient prefrontal executive function compared to a more rapidly developing subcortical motivation system. We examined executive function as assessed by working memory ability in a community sample of youth (n = 387, ages 10 to 12…
Descriptors: Conceptual Tempo, Intervention, Structural Equation Models, Early Adolescents
Vieira, Edward T., Jr.; Grantham, Susan – Educational Psychology, 2011
In this study, the authors attempted to examine the roles of trait autonomy, trait self-efficacy, important goal-related task engagement and gender in predicting whether undergraduate university students are willing to set difficult goals. One hundred and thirty-six undergraduate communications students from the North-Eastern USA completed an…
Descriptors: Structural Equation Models, Self Efficacy, Factor Analysis, Goal Orientation
Zhang, Xiao; Chen, Huichang – Journal of Genetic Psychology, 2010
To examine the reciprocal influences between mother-child and father-child relationships, the authors analyzed cross-lagged longitudinal data on children's relationships with both parents using a structural equation modeling approach. Mothers and fathers of 100 Chinese preschoolers aged 2-3 years filled in the Child-Parent Relationship Scale (R.…
Descriptors: Mothers, Structural Equation Models, Conflict, Parent Child Relationship
Diestel, Stefan; Schmidt, Klaus-Helmut – Journal of Vocational Behavior, 2010
Two specific sources of stress at work have recently received increasing attention in organizational stress research: emotional dissonance (ED) and self-control demands (SCDs). Both theoretical arguments and experimental findings in basic research strongly suggest that ED and different SCDs draw on a common limited regulatory resource.…
Descriptors: Stress Variables, Structural Equation Models, Anxiety, Burnout
Berger, Jean-Louis; Karabenick, Stuart A. – Learning and Instruction, 2011
Considerable evidence indicates that student motivation and use of learning strategies are related. There is insufficient understanding, however, about their reciprocal effects--whether motivation affects strategy use, the converse, or whether the effects are bidirectional--and which components of motivation and strategies are involved. A two-wave…
Descriptors: Self Efficacy, Learning Strategies, Student Motivation, Grade 9