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Giota, Joanna – Scandinavian Journal of Educational Research, 2010
In this study, first- and second-order confirmatory factor analyses were used to investigate the structure of the different types of academic, social, and future goals pursued by adolescents in school, and whether goals can be hierarchically organized. A multiple goals perspective on goal preferences was adopted. The study was based on 10,000…
Descriptors: Student Motivation, Adolescents, Foreign Countries, Factor Analysis
Mayer, Matthew J. – Journal of School Violence, 2010
The 1995-2005 School Crime Supplement datasets were analyzed using structural equation modeling. Converging evidence across multiple analyses suggests that secure school building policies may not be systematically linked to school disorder and may be more a reactive measure in response to other concerns. Most importantly, measures of incivility…
Descriptors: Violence, Crime, Structural Equation Models, School Buildings
Montgomery, Guy H.; Hallquist, Michael N.; Schnur, Julie B.; David, Daniel; Silverstein, Jeffrey H.; Bovbjerg, Dana H. – Journal of Consulting and Clinical Psychology, 2010
Objective: The present study was designed to test the hypotheses that response expectancies and emotional distress mediate the effects of an empirically validated presurgical hypnosis intervention on postsurgical side effects (i.e., pain, nausea, and fatigue). Method: Women (n = 200) undergoing breast-conserving surgery (mean age = 48.50 years;…
Descriptors: Control Groups, Fatigue (Biology), Intervention, Structural Equation Models
Geske, Andrejs; Ozola, Antra – Online Submission, 2009
The results of IEA (The International Association for the Evaluation of Educational Achievement) PIRLS 2006 (Progress in International Reading Literacy Study) has showed that Latvia has the 6th largest gender gap in reading literacy scores and that is an indication of a serious problem of education in this country. The purpose of the paper is to…
Descriptors: Reading Achievement, Gender Differences, Context Effect, Educational Environment
Daniels, Lia M.; Stupnisky, Robert H.; Pekrun, Reinhard; Haynes, Tara L.; Perry, Raymond P.; Newall, Nancy E. – Journal of Educational Psychology, 2009
Affect and emotions are frequently seen as outcomes of mastery and performance goals, but affective experiences may also predict goal adoption. In a predictive study (N = 669 first-year college students), the authors used structural equation modeling to estimate relationships from 2 initial affective experiences to mastery and performance-approach…
Descriptors: College Freshmen, Structural Equation Models, Goal Orientation, Psychological Patterns
Saris, Willem E.; Satorra, Albert; van der Veld, William M. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Assessing the correctness of a structural equation model is essential to avoid drawing incorrect conclusions from empirical research. In the past, the chi-square test was recommended for assessing the correctness of the model but this test has been criticized because of its sensitivity to sample size. As a reaction, an abundance of fit indexes…
Descriptors: Structural Equation Models, Validity, Goodness of Fit, Evaluation Methods
Klassen, Robert M.; Ang, Rebecca P.; Chong, Wan Har; Krawchuk, Lindsey L.; Huan, Vivien S.; Wong, Isabella Y. F.; Yeo, Lay See – Journal of Research on Adolescence, 2009
In this study, we explore academic procrastination and associated motivation variables in 612 adolescents from Canada and Singapore. Few studies have explored adolescent procrastination and no previous studies have investigated adolescent procrastination using a cross-cultural framework. Singaporean adolescents reported higher levels of…
Descriptors: Adolescents, Cross Cultural Studies, Self Efficacy, Structural Equation Models
Katt, James A.; Speranza, Linda; Shore, Wendy; Saenz, Karen H.; Witta, E. Lea – Journal of Genetic Psychology, 2009
An existing large data set, the Health and Retirement Study (HRS) with the subsequent addition of the Consumption and Activities Mail Survey (CAMS) data, provides a rich data set for the examination of the activities of older adults. In this study HRS and CAMS data are used to examine relationships between various activities of daily living (ADLs)…
Descriptors: Structural Equation Models, Older Adults, Activities, Daily Living Skills
Popper, Micha; Amit, Karin – Journal of Genetic Psychology, 2009
Addressing psychological literature's deficiency in research on the early development of leaders in everyday life (e.g., leaders in the workplace, leaders in social settings, leaders in organizational settings), this study assumed that central psychological capacities required for such leaders can be predicted and explained by J. Bowlby's (1969)…
Descriptors: Structural Equation Models, Infants, Attachment Behavior, Psychology
Brown, Robert M.; Mazzarol, Timothy William – Higher Education: The International Journal of Higher Education and Educational Planning, 2009
This paper outlines the findings of a study employing a partial least squares (PLS) structural equation methodology to test a customer satisfaction model of the drivers of student satisfaction and loyalty in higher education settings. Drawing upon a moderately large sample of students enrolled in four "types" of Australian universities,…
Descriptors: Higher Education, Structural Equation Models, Least Squares Statistics, Student Attitudes
Hawdon, James; Ryan, John – Crime & Delinquency, 2009
A neighborhood-level model of crime that connects the central dimensions of social capital with specific forms of social control is developed. The proposed model is tested using a structural equation model that predicts changes in empirical Bayes log odds of neighborhood victimization rates between 2000 and 2001 in 41 neighborhoods in South…
Descriptors: Neighborhoods, Crime, Social Control, Social Capital
Mooijaart, Ab; Satorra, Albert – Psychometrika, 2009
In this paper, we show that for some structural equation models (SEM), the classical chi-square goodness-of-fit test is unable to detect the presence of nonlinear terms in the model. As an example, we consider a regression model with latent variables and interactions terms. Not only the model test has zero power against that type of…
Descriptors: Structural Equation Models, Geometric Concepts, Goodness of Fit, Models
Bus, A. G.; Out, D. – Reading and Writing: An Interdisciplinary Journal, 2009
Even though the acquisition of early literacy skills obviously depends on stimuli and incentives in children's environment we may expect that genes define the constraints for acquiring some or all early literacy skills. Therefore behavior genetic analyses were carried out on twin data including 27 identical and 39 same sex dizygotic twins, 4 years…
Descriptors: Twins, Structural Equation Models, Genetics, Emergent Literacy
Bai, Yun; Poon, Wai-Yin – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Two-level data sets are frequently encountered in social and behavioral science research. They arise when observations are drawn from a known hierarchical structure, such as when individuals are randomly drawn from groups that are randomly drawn from a target population. Although 2-level data analysis in the context of structural equation modeling…
Descriptors: Structural Equation Models, Data Analysis, Simulation, Goodness of Fit
Bullock-Yowell, Emily; Katz, Sheba P.; Reardon, Robert C.; Peterson, Gary W. – Professional Counselor, 2012
The respective roles of social cognitive career theory and cognitive information processing in career exploratory behavior were analyzed. A verified path model shows cognitive information processing theory's negative career thoughts inversely predict social cognitive career theory's career problem-solving self-efficacy, which predicts career…
Descriptors: Problem Solving, Self Efficacy, Career Development, Social Cognition