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Peer reviewedFan, Xitao – Journal of Experimental Education, 2001
Studied the effects of parental involvement on students' academic growth during high school using data from the National Education Longitudinal Study of 1988 with latent growth curve analysis in the framework of structural equation modeling. Discusses the ways in which parental involvement was found to be multidimensional. (SLD)
Descriptors: Academic Achievement, High School Students, High Schools, Parent Participation
Peer reviewedDiseth, Age – Scandinavian Journal of Educational Research, 2001
Administered the Approaches and Study Skills Inventory for Students (ASSIST) (N. Entwhistle and P. Ramsden, 1983) to 573 undergraduates to analyze a Norwegian version of this inventory. Structural equation modeling techniques reveal the usefulness of this instrument as a research took for the assessment of approaches to learning among Norwegian…
Descriptors: Foreign Countries, Learning Strategies, Structural Equation Models, Study Skills
Peer reviewedLee, Sik-Yum; Song, Xin-Yuan – Multivariate Behavioral Research, 2001
Demonstrates the use of the well-known Bayes factor in the Bayesian literature for hypothesis testing and model comparison in general two-level structural equation models. Shows that the proposed method is flexible and can be applied to situations with a wide variety of nonnested models. (SLD)
Descriptors: Bayesian Statistics, Comparative Analysis, Goodness of Fit, Hypothesis Testing
Peer reviewedLinares, L. Oriana; Heeren, Timothy; Bronfman, Elisa – Child Development, 2001
Structural equation modeling was used to examine how maternal distress mediated the link between exposure to community violence (CV) and development of early child behavior problems. Findings indicated that direct CV-early child behavior problems path diminished when maternal distress was included in the model, after controlling for maternal SES…
Descriptors: Behavior Problems, Models, Mothers, Parent Influence
Cerutti, D. T.; Staddon, J. E. R. – Journal of the Experimental Analysis of Behavior, 2004
Three experiments with pigeons studied the relation between time and rate measures of behavior under conditions of changing preference. Experiment 1 studied a concurrent chain schedule with random-interval initial links and fixed-interval terminal links; Experiment 2 studied a multiple chained random-interval fixed-interval schedule; and…
Descriptors: Intervals, Measurement, Experiments, Reinforcement
Peer reviewedCramond, Bonnie; Matthews-Morgan, Juanita; Bandalos, Deborah; Zuo, Li – Gifted Child Quarterly, 2005
This article updates information about the Torrance Tests of Creative Thinking (TTCT) by reporting on predictive validity data from the most recent data collection point in Torrance's longitudinal studies. First, we outline the background of the tests and changes in scoring over the years. Then, we detail the results of the analyses of the 40-year…
Descriptors: Predictive Validity, Longitudinal Studies, Creative Thinking, Tests
Peer reviewedYeh, Hsiu-Chen; Lempers, Jacques D. – Journal of Youth and Adolescence, 2004
Utilizing longitudinal, 3-wave data collected from multiple informants (fathers, mothers, and target children) in 374 families, the potential effects of sibling relationships on adolescent development across early and middle adolescence were investigated. Adolescents who perceived their sibling relationships more positively at Time 1 tended to…
Descriptors: Adolescents, Structural Equation Models, Siblings, Friendship
Cheung, Mike W. L.; Chan, Wai – Psychological Methods, 2005
To synthesize studies that use structural equation modeling (SEM), researchers usually use Pearson correlations (univariate r), Fisher z scores (univariate z), or generalized least squares (GLS) to combine the correlation matrices. The pooled correlation matrix is then analyzed by the use of SEM. Questionable inferences may occur for these ad hoc…
Descriptors: Inferences, Meta Analysis, Least Squares Statistics, Structural Equation Models
Huth-Bocks, Alissa C.; Levendosky, Alytia A.; Bogat, G. Anne; von Eye, Alexander – Child Development, 2004
This prospective study examined the effects of maternal characteristics, social support, and risk factors on infant-mother attachment in a heterogeneous sample. Two hundred and six women between the ages of 18 and 40 were interviewed during their last trimester of pregnancy and 1 year postpartum. Structural equation modeling revealed that maternal…
Descriptors: Infants, Females, Structural Equation Models, Risk
Martens, Matthew P.; Haase, Richard F. – Counseling Psychologist, 2006
Structural equation modeling (SEM) is a data-analytic technique that allows researchers to test complex theoretical models. Most published applications of SEM involve analyses of cross-sectional recursive (i.e., unidirectional) models, but it is possible for researchers to test more complex designs that involve variables observed at multiple…
Descriptors: Structural Equation Models, Counseling Psychology, Researchers, Models
French, Brian F.; Finch, W. Holmes – Structural Equation Modeling: A Multidisciplinary Journal, 2006
Confirmatory factor analytic (CFA) procedures can be used to provide evidence of measurement invariance. However, empirical evaluation has not focused on the accuracy of common CFA steps used to detect a lack of invariance across groups. This investigation examined procedures for detection of test structure differences across groups under several…
Descriptors: Factor Analysis, Structural Equation Models, Evaluation Criteria, Error of Measurement
Scharlach, Andrew; Li, Wei; Dalvi, Tapashi B. – Family Relations, 2006
The present study used structural equation modeling to examine the potential mediating effect of family conflict on caregiver strain in a randomly drawn household sample of 650 adults with primary care responsibility for an adult age 50 or older with a mental disability. Caregiver strain was directly influenced by the conflict, disagreements, and…
Descriptors: Family Relationship, Conflict, Caregivers, Stress Variables
Schreiber, James B.; Nora, Amaury; Stage, Frances K.; Barlow, Elizabeth A.; King, Jamie – Journal of Educational Research, 2006
The authors provide a basic set of guidelines and recommendations for information that should be included in any manuscript that has confirmatory factor analysis or structural equation modeling as the primary statistical analysis technique. The authors provide an introduction to both techniques, along with sample analyses, recommendations for…
Descriptors: Structural Equation Models, Guidelines, Factor Analysis, Statistical Analysis
Sivo, Stephen A.; Xitao, Fan; Witta, E. Lea; Willse, John T. – Journal of Experimental Education, 2006
This study is a partial replication of L. Hu and P. M. Bentler's (1999) fit criteria work. The purpose of this study was twofold: (a) to determine whether cut-off values vary according to which model is the true population model for a dataset and (b) to identify which of 13 fit indexes behave optimally by retaining all of the correct models while…
Descriptors: Structural Equation Models, Goodness of Fit, Criteria, Sample Size
Gionta, Dana A.; Harlow, Lisa L.; Loitman, Jane E.; Leeman, Joanne M. – Structural Equation Modeling, 2005
Three structural equation models of communication between family members and medical staff were examined to understand relations among staff accessibility, inhibitory family attitudes, getting communication needs met, perceived stress, and satisfaction with communication. Compared to full and direct models, a mediational model fit best in which…
Descriptors: Patients, Family Attitudes, Family Needs, Structural Equation Models

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