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Beets, Michael W.; Pitetti, Kenneth H.; Forlaw, Loretta – American Journal of Health Behavior, 2007
Objective: To examine the role of social support (SS) and self-efficacy (SE) for physical activity (PA) in rural high school girls (N = 259, 15.5+1.2yrs). Methods: Using structural equation modeling, the relationships among PA, SS for PA from mother, father, and peers, and SE for overcoming barriers, seeking support, and resisting competing…
Descriptors: Social Support Groups, Physical Activities, Females, Structural Equation Models
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Kember, David; Leung, Doris Y. P.; Ma, Rosa S. F. – Research in Higher Education, 2007
There has been wide recognition that today's graduates need the type of generic capabilities necessary for lifelong learning. However, the mechanism by which universities can develop these generic skills is not clearly established. This study aimed to investigate the mechanism for their development. Structural equation modeling (SEM) was used to…
Descriptors: Structural Equation Models, Focus Groups, Lifelong Learning, Learning Processes
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Du Rocher Schudlich, Tina D.; Cummings, E. Mark – Journal of Abnormal Child Psychology, 2007
Dimensions of martial conflict, children's emotional security regarding interparental conflict, and parenting style were examined as mediators between parental dysphoria and child adjustment. A community sample of 262 children, ages 8-16, participated with their parents. Behavioral observations were made of parents' interactions during marital…
Descriptors: Psychological Needs, Child Rearing, Structural Equation Models, Parenting Styles
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Wang, Zhongmiao; Thompson, Bruce – Journal of Experimental Education, 2007
In this study the authors investigated the use of 5 (i.e., Claudy, Ezekiel, Olkin-Pratt, Pratt, and Smith) R[squared] correction formulas with the Pearson r[squared]. The authors estimated adjustment bias and precision under 6 x 3 x 6 conditions (i.e., population [rho] values of 0.0, 0.1, 0.3, 0.5, 0.7, and 0.9; population shapes normal, skewness…
Descriptors: Effect Size, Correlation, Mathematical Formulas, Monte Carlo Methods
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Vranceanu, Ana-Maria; Hobfoll, Stevan E.; Johnson, Robert J. – Child Abuse & Neglect: The International Journal, 2007
Objective: This retrospective, cross-sectional study explored the hypothesis that multiple forms of child abuse and neglect (child multi-type maltreatment; CMM) would be associated with women's lower social support and higher stress in adulthood, and that this, in turn, would amplify their vulnerability to symptoms of depression and posttraumatic…
Descriptors: Females, Adults, Child Neglect, Child Abuse
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Plunkett, Scott W.; Abarca-Mortensen, Sandra; Behnke, Andrew O.; Sands, Tovah – Hispanic Journal of Behavioral Sciences, 2007
The purposes of this research brief were to examine (a) whether youth reports of neighborhood qualities were significantly related to census data at the block group, measuring the same structural qualities and (b) whether the structural qualities were related to youth development either directly or indirectly through youth perceptions. Data were…
Descriptors: Structural Equation Models, Self Efficacy, Neighborhoods, Adolescents
Fan, Xitao; And Others – 1996
A Monte Carlo simulation study was conducted to investigate the effects of sample size, estimation method, and model specification on structural equation modeling (SEM) fit indices. Based on a balanced 3x2x5 design, a total of 6,000 samples were generated from a prespecified population covariance matrix, and eight popular SEM fit indices were…
Descriptors: Estimation (Mathematics), Goodness of Fit, Mathematical Models, Monte Carlo Methods
Thompson, Bruce; Fan, Xitao – 1998
This study empirically investigated bootstrap bias estimation in the area of structural equation modeling (SEM). Three correctly specified SEM models were used under four different sample size conditions. Monte Carlo experiments were carried out to generate the criteria against which bootstrap bias estimation should be judged. For SEM fit indices,…
Descriptors: Estimation (Mathematics), Goodness of Fit, Monte Carlo Methods, Sample Size
Kim, Se-Kang; Davison, Mark L. – 2000
This study described an explicit multidimensional scaling (MDS) model for profile data, the Profile Analysis via Multidimensional Scaling (PAMS) model. It also illustrated the application of this model to the study of the structure of cognitive ability patterns using the Woodcock-Johnson Psychoeducational Battery-Revised (WJPB-R; 1989; 1991) and…
Descriptors: Adults, Cognitive Ability, Factor Analysis, Factor Structure
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Duncan, Terry E.; Duncan, Susan C.; Li, Fuzhong – Structural Equation Modeling, 1998
Presents an application of latent growth curve methodology to the analysis of longitudinal developmental change in alcohol consumption of 586 young adults, illustrating three approaches to the analysis of missing data: (1) multiple-sample structural equation modeling procedures; (2) raw maximum likelihood analyses; and (3) multiple modeling and…
Descriptors: Algorithms, Change, Comparative Analysis, Drinking
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Papa, Frank J.; And Others – Structural Equation Modeling, 1997
Chest pain was identified as a specific medical problem space, and disease classes were modeled to define it. Results from a test taken by 628 medical residents indicate a second-order factor structure that suggests that chest pain is a multidimensional problem space. Implications for medical education are discussed. (SLD)
Descriptors: Classification, Clinical Diagnosis, Factor Structure, Knowledge Level
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Hong, Sehee; Malik, Mary L.; Lee, Min-Kyu – Educational and Psychological Measurement, 2003
Used latent means analysis in the framework of structural equation modeling to explore the factor structure and gender differences associated with the Personal Style Inventory (PSI; C. Robins and others, 1994) with 508 Korean undergraduates. Results support the cross-cultural stability of the PSI factor structure. Women had higher scores than men…
Descriptors: Cross Cultural Studies, Factor Structure, Foreign Countries, Higher Education
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Luo, Dasen; Thompson, Lee A.; Detterman, Douglas K. – Intelligence, 2003
Fitted structural equation models to covariances among 9 cognitive abilities Test variables, 11 intelligence test variables, and 3 achievement test scaled scores of 532 primary school children in a twin studies project. Results suggest that individual differences in mental speed are a main causal factor underlying correlation between general…
Descriptors: Academic Achievement, Causal Models, Correlation, Elementary Education
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Holbert, R. Lance; Stephenson, Michael T. – Human Communication Research, 2002
Notes that structural equation modeling (SEM) is a viable multivariate tool used by communication researchers for the past quarter century. Summarizes the use of this technique from 1995-2000 in 37 communication-based academic journals. Identifies and critically assesses 3 unique methods for testing structural relationships via SEM in terms of the…
Descriptors: Communication (Thought Transfer), Communication Research, Higher Education, Multivariate Analysis
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Teachman, Jay D. – Journal of Family Issues, 1995
Argues that data on siblings provide a way to account for the impact of unmeasured, omitted variables on relationships of interest because families form a sort of natural experiment, with similar experiences and common genetic heritage. Proposes a latent-variable structural equation approach to the problem, which provides estimates of both within-…
Descriptors: Environmental Influences, Experiments, Factor Analysis, Family Influence
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