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Nevitt, Jonathan; Hancock, Gregory R. – Multivariate Behavioral Research, 2004
Through Monte Carlo simulation, small sample methods for evaluating overall data-model fit in structural equation modeling were explored. Type I error behavior and power were examined using maximum likelihood (ML), Satorra-Bentler scaled and adjusted (SB; Satorra & Bentler, 1988, 1994), residual-based (Browne, 1984), and asymptotically…
Descriptors: Statistical Data, Sample Size, Monte Carlo Methods, Structural Equation Models
Lee, Sik-Yum; Song, Xin-Yuan – Multivariate Behavioral Research, 2004
The main objective of this article is to investigate the empirical performances of the Bayesian approach in analyzing structural equation models with small sample sizes. The traditional maximum likelihood (ML) is also included for comparison. In the context of a confirmatory factor analysis model and a structural equation model, simulation studies…
Descriptors: Sample Size, Factor Analysis, Structural Equation Models, Comparative Analysis
Mamon, Rogemar S. – International Journal of Mathematical Education in Science and Technology, 2004
Within the general framework of a multifactor term structure model, the fundamental partial differential equation (PDE) satisfied by a default-free zero-coupon bond price is derived via a martingale-oriented approach. Using this PDE, a result characterizing a model belonging to an exponential affine class is established using only a system of…
Descriptors: Factor Analysis, Structural Equation Models, Bond Issues, Computation
Lincoln, Karen D.; Chatters, Linda M.; Taylor, Robert Joseph – Journal of Marriage and Family, 2005
Structural equation modeling was used to examine the relationships among stress, social support, negative interaction, and mental health in a sample of African American men and women between ages 18 and 54 (N = 591) from the National Comorbidity Study. The study findings indicated that social support decreased the number of depressive symptoms,…
Descriptors: African Americans, Interpersonal Relationship, Interaction, Structural Equation Models
Csizer, Kata; Dornyei, Zoltan – Modern Language Journal, 2005
Language learning motivation is a complex, composite construct, and although past research has identified a number of its key components, the interrelationship of these components has often been subject to debate. Similarly, the exact contribution of the various motivational components to learning behaviors and learning achievement has also been…
Descriptors: Foreign Countries, Structural Equation Models, Learning Motivation, Second Language Learning
Kahn, Jeffrey H. – Counseling Psychologist, 2005
The author reacts to the three core articles in the Scientific Forum of the May 2005 issue of "The Counseling Psychologist" about institutional research productivity, the use of theory-driven research, and the application of structural equation modeling to research in counseling psychology. To have a research base that maximizes divergent…
Descriptors: Structural Equation Models, Productivity, Institutional Research, Counseling Psychology
Schmittmann, Verena D.; Dolan, Conor V.; van der Maas, Han L. J.; Neale, Michael C. – Multivariate Behavioral Research, 2005
Van de Pol and Langeheine (1990) presented a general framework for Markov modeling of repeatedly measured discrete data. We discuss analogical single indicator models for normally distributed responses. In contrast to discrete models, which have been studied extensively, analogical continuous response models have hardly been considered. These…
Descriptors: Markov Processes, Models, Responses, Modeling (Psychology)
Schweizer, Karl; Moosbrugger, Helfried – Intelligence, 2004
The paper reports on an investigation of attention and working memory as sources of intelligence. The investigation was concentrated on the relatedness of attention and working memory as predictors of intelligence and on the structure underlying the prediction. In a sample of 120 participants, intelligence was assessed by the Advanced Progressive…
Descriptors: Intelligence, Memory, Predictor Variables, Attention
Gaylord-Harden, Noni K.; Ragsdale, Brian L.; Mandara, Jelani; Richards, Maryse H.; Petersen, Anne C. – Journal of Youth and Adolescence, 2007
Existing research leaves a gap in explaining why African American adolescents do not exhibit more anxiety and depression than other youth, at the same time that they experience more contextual risk factors. The current study examined the roles of social support as well as possible mediators self-esteem and ethnic identity (sense of belonging to…
Descriptors: Gender Differences, Structural Equation Models, Ethnicity, Depression (Psychology)
Chen, Greg – Journal of School Violence, 2007
The study develops a school safety and student achievement model, incorporating the concepts of student background, school structure, school culture, school disorder, and student academic achievement, and fits it to 613 elementary schools in New York City, using Structural Equations Modeling technique. The model fits the data well based on both…
Descriptors: Student Behavior, Elementary Schools, School Culture, School Safety
Lippke, Sonia; Nigg, Claudio R.; Maddock, Jay E. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
This is the first study to test whether the stages of change of the transtheoretical model are qualitatively different through exploring discontinuity patterns in theory of planned behavior (TPB) variables using latent multigroup structural equation modeling (MSEM) with AMOS. Discontinuity patterns in terms of latent means and prediction patterns…
Descriptors: Physical Activities, Structural Equation Models, Physical Activity Level, Prediction
Torquati, Julia C.; Raikes, Helen; Huddleston-Casas, Catherine A. – Early Childhood Research Quarterly, 2007
The purposes of this study were to present a conceptual model for selection into the early childhood profession and to test the model using contemporaneous assessments. A stratified random sample of center-based child care providers in 4 Midwestern states (n=964) participated in a telephone interview, and 223 were also assessed with the Early…
Descriptors: Teacher Education, Teacher Motivation, Compensation (Remuneration), Work Environment
Chouinard, Roch; Karsenti, Thierry; Roy, Normand – British Journal of Educational Psychology, 2007
Background: Research has shown that motivation is a key factor in the learning process as well as in school achievement. In essence, a number of researchers have highlighted the close link between motivation and achievement-related behaviours such as effort. Aims: The present study aims to acquire more specific information concerning the relations…
Descriptors: Student Motivation, Learning Processes, Academic Achievement, Teaching Methods
Johnson, Bruce; Stevens, Joseph J.; Zvoch, Keith – Educational and Psychological Measurement, 2007
Scores from a revised version of the School Level Environment Questionnaire (SLEQ) were validated using a sample of teachers from a large school district. An exploratory factor analysis was used with a randomly selected half of the sample. Five school environment factors emerged. A confirmatory factor analysis was run with the remaining half of…
Descriptors: Measures (Individuals), Statistical Analysis, Educational Environment, Structural Equation Models
Harold, Gordon T.; Aitken, Jessica J.; Shelton, Katherine H. – Journal of Child Psychology and Psychiatry, 2007
Background: Previous research suggests a link between inter-parental conflict and children's psychological development. Most studies, however, have tended to focus on two broad indices of children's psychological adaptation (internalizing symptoms and externalizing problems) in considering the effects of inter-parental conflict on children's…
Descriptors: Intervention, Aggression, Structural Equation Models, Conflict