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Wauters, Loes N.; Knoors, Harry – Journal of Deaf Studies and Deaf Education, 2008
This article examines social integration of deaf children in inclusive settings in The Netherlands. Eighteen Grade 1-5 deaf children and their 344 hearing classmates completed 2 sociometric tasks, peer ratings and peer nomination, to measure peer acceptance, social competence, and friendship relations. Deaf and hearing children were found to be…
Descriptors: Prosocial Behavior, Social Integration, Structural Equation Models, Deafness
Chu, Regina Ju-chun – Computers & Education, 2010
Gender and age differences in the effects of e-learning, including students' satisfaction and Internet self-efficacy, have been supported in prior research. What is less understood is how these differences are shaped, especially for higher aged adults. This article examines the utility of family support (tangible and emotional) and Internet…
Descriptors: Electronic Learning, Structural Equation Models, Self Efficacy, Adults
Pantalone, David W.; Hessler, Danielle M.; Simoni, Jane M. – Journal of Consulting and Clinical Psychology, 2010
Objective: We examined mental health pathways between interpersonal violence (IPV) and health-related outcomes in HIV-positive sexual minority men engaged with medical care. Method: HIV-positive gay and bisexual men (N = 178) were recruited for this cross-sectional study from 2 public HIV primary care clinics that treated outpatients in an urban…
Descriptors: Medical Services, Structural Equation Models, Posttraumatic Stress Disorder, Quality of Life
Diemer, Matthew A.; Wang, Qiu; Moore, Traymanesha; Gregory, Shannon R.; Hatcher, Keisha M.; Voight, Adam M. – Developmental Psychology, 2010
Structural barriers constrain marginalized youths' development of work salience and vocational expectations. Sociopolitical development (SPD), the consciousness of, and motivation to reduce, sociopolitical inequality, may facilitate the negotiation of structural constraints. A structural model of SPD's impact on work salience and vocational…
Descriptors: Social Mobility, Youth, Asian Americans, African Americans
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
Peer reviewedBabyak, 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
Peer reviewedRaykov, 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
Peer reviewedShipley, 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
Peer reviewedLi, 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
Peer reviewedBilliet, 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
Peer reviewedWall, 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
Peer reviewedRaykov, Tenko – Structural Equation Modeling, 2001
Discusses a method, based on bootstrap methodology, for obtaining an approximate confidence interval for the difference in root mean square error of approximation of two structural equation models. Illustrates the method using a numerical example. (SLD)
Descriptors: Goodness of Fit, Structural Equation Models
Mehta, Paras D.; Neale, Michael C.; Flay, Brian R. – Psychological Methods, 2004
A didactic on latent growth curve modeling for ordinal outcomes is presented. The conceptual aspects of modeling growth with ordinal variables and the notion of threshold invariance are illustrated graphically using a hypothetical example. The ordinal growth model is described in terms of 3 nested models: (a) multivariate normality of the…
Descriptors: Structural Equation Models, Intervals, Multivariate Analysis
Jackson, Dennis L. – Structural Equation Modeling: A Multidisciplinary Journal, 2003
A number of authors have proposed that determining an adequate sample size in structural equation modeling can be aided by considering the number of parameters to be estimated. While this advice seems plausible, little empirical support appears to exist. A previous study by Jackson (2001), failed to find support for this hypothesis, however, there…
Descriptors: Sample Size, Structural Equation Models, Computation

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