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de Leeuw, Rebecca N. H.; Scholte, Ron H. J.; Harakeh, Zeena; van Leeuwe, Jan F. J.; Engels, Rutger C. M. E. – Journal of Youth and Adolescence, 2008
In this study, we investigated whether parental smoking-specific communication is related to adolescents' friendship-selection processes. Furthermore, we investigated whether adolescents and their best friends influence each other over time, and what role parents play in this process. In the present study we used data from the Family and Health…
Descriptors: Smoking, Structural Equation Models, Friendship, Older Adults
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Martens, Matthew P.; Martin, Jessica L.; Hatchett, E. Suzanne; Fowler, Roneferiti M.; Fleming, Kristie M.; Karakashian, Michael A.; Cimini, M. Dolores – Journal of Counseling Psychology, 2008
Approximately 40% of college students reported engaging in heavy episodic or "binge" drinking in the 2 weeks prior to being surveyed. Research indicates that college students suffering from depression are more likely to report experiencing negative consequences related to their drinking than other students are. The reasons for this…
Descriptors: College Students, Structural Equation Models, Drinking, Depression (Psychology)
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Tang, Mei; Pan, Wei; Newmeyer, Mark D. – Professional School Counseling, 2008
This article explores the factors influencing high school students' career aspirations with a study analyzing 141 high school students. The Social Cognitive Career Development Model was utilized to examine the interactive relationships among learning experiences, career self-efficacy, outcome expectations, career interests, and career choices. The…
Descriptors: High Schools, Intervention, Structural Equation Models, Self Efficacy
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Coyle, Thomas R.; Pillow, David R. – Intelligence, 2008
This research examined whether the SAT and ACT would predict college grade point average (GPA) after removing g from the tests. SAT and ACT scores and freshman GPAs were obtained from a university sample (N=161) and the 1997 National Longitudinal Study of Youth (N=8984). Structural equation modeling was used to examine relationships among g, GPA,…
Descriptors: Intelligence, Grade Point Average, Structural Equation Models, Predictive Validity
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Parker, Philip D.; Martin, Andrew J. – Learning and Individual Differences, 2008
While much research has outlined the importance of intra-psychic factors in predicting workplace success, it is rare that attention is given to the development of these factors in training for human service professions (e.g. psychology, clergy, nursing). Accordingly, the present study explores differences in self-concept, a key intra-psychic…
Descriptors: Human Services, Structural Equation Models, Personality Traits, Personality Measures
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Usluel, Yasemin Kocak; Askar, Petek; Bas, Turgay – Educational Technology & Society, 2008
This study focuses on Information and Communication Technologies (ICT) usage, which is the indicator of diffusion. A model composed of the variables which can explain ICT usage in Turkish higher education is established and tested within the study. The two dimensions of ICT usage are considered: instructional and managerial. The data collected…
Descriptors: Foreign Countries, Internet, College Faculty, Information Technology
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Chamorro-Premuzic, Tomas; Ahmetoglu, Gorkan; Furnham, Adrian – Learning and Individual Differences, 2008
This study attempted a hierarchical integration of several dispositional determinants of test anxiety (TA) [Sarason, I.G. (1984). "Stress, anxiety and cognitive interference: Reactions to tests." "Journal of Personality and Social Psychology," 46, 929-938.], namely the Big Five personality traits [Costa, P.T. Jr., & McCrae,…
Descriptors: Personality Traits, Individual Differences, Psychological Evaluation, Structural Equation Models
Baloglu, Mustafa – 1999
This paper provides theoretical and practical information about using structural equation modeling (SEM) techniques. The first section discusses the theory of SEM, including five general steps: (1) model specification; (2) model identification; (3) model estimation; (4) testing model fit; and (5) model respecification. The second section applies…
Descriptors: Structural Equation Models, Theory Practice Relationship
Kim, Se-Kang – 2002
The effect of bootstrapping was studied by examining whether major profile patterns were replicated when sample sizes were reduced. Profile patterns estimated from the original sample (n=645) of the Wechsler Preschool and Primary Scale of IntelligenceThird Edition (WPPSI-III) Standardization Data were considered major profiles. For bootstrapping,…
Descriptors: Profiles, Sample Size, Structural Equation Models
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Babyak, Michael A.; Green, Samuel B. – Multivariate Behavioral Research, 1997
Contrasting positions about the evaluation of multiple tests of constraints and control of Type I errors in structural equation modeling (SEM) are presented. It is argued that researchers should consider controlling for Type I errors in evaluating multiple tests of constraints for other than exploratory analyses. (SLD)
Descriptors: Error of Measurement, Structural Equation Models
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Raykov, Tenko; Shrout, Patrick E. – Structural Equation Modeling, 2002
Discusses a method for obtaining point and interval estimates of reliability for composites of measures with a general structure. The approach is based on fitting a correspondingly constrained structural equation model and generalizes earlier covariance structure analysis methods for scale reliability estimation with congeneric tests. (SLD)
Descriptors: Estimation (Mathematics), Reliability, Structural Equation Models
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Shipley, Bill – Structural Equation Modeling, 2000
Introduces a new inferential test for acyclic structural equation models (SEM) without latent variables or correlated errors. The test is based on the independence relations predicted by the directed acyclic graph of the SEMs, as given by the concept of d-separation. A wide range of distributional assumptions and structural functions can be…
Descriptors: Graphs, Statistical Inference, Structural Equation Models
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Li, Fuzhong; Duncan, Terry E.; Acock, Alan – Structural Equation Modeling, 2000
Presents an extension of the method of estimating interaction effects among latent variables to latent growth curve models developed by K. Joreskog and F. Yang (1996). Illustrates the procedure and discusses results in terms of practical and statistical problems associated with interaction analyses in latent curve models and structural equation…
Descriptors: Estimation (Mathematics), Interaction, Structural Equation Models
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Billiet, Jaak B.; McClendon, McKee J. – Structural Equation Modeling, 2000
Studied the measurement of acquiescence in balanced scales using a structural equation modeling approach with subsamples of 986 and 992 from the same population of Belgian adults interviewed about ethnic prejudice. The strong relation in both populations of the latent style factor with a variable "sum of agreements" supports the idea…
Descriptors: Adults, Foreign Countries, Structural Equation Models
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Wall, Melanie M.; Amemiya, Yasuo – Journal of Educational and Behavioral Statistics, 2001
Considers the estimation of polynomial structural models and shows a limitation of an existing method. Introduces a new procedure, the generalized appended product indicator procedure, for nonlinear structural equation analysis. Addresses statistical issues associated with the procedure through simulation. (SLD)
Descriptors: Estimation (Mathematics), Simulation, Structural Equation Models
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