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Peer reviewedQuintana, Stephen M.; Maxwell, Scott E. – Counseling Psychologist, 1999
Reviews recent developments in structural equation modeling (SEM). Discusses issues critical to designing and evaluating SEM studies and recent technological developments. Examines innovations in applying SEM to different research contexts and designs. Also discusses procedures for redressing common problems and misunderstandings in the…
Descriptors: Counseling, Evaluation, Models, Research
Peer reviewedSchweizer, Karl – Intelligence, 2001
Studied the contribution of preattentive processes to the cognitive speed-ability relationship for 80 participants. Results reveal an increase in ability-related variances due to the stimulation of preattentive processes. Coefficients for a structural equation model indicated that preattentive processes exerted a stronger effect on cognitive…
Descriptors: Ability, Attention, Cognitive Processes, College Students
Wilke, Dina J.; Kamata, Akihito; Cash, Scottye J. – Child Abuse & Neglect: The International Journal, 2005
Objectives: Children are often considered a primary motivator for women seeking substance abuse treatment. This study tested a model predicting treatment motivation in substance-abusing mothers. Methods: This study was a secondary analysis of the Drug Abuse Treatment Outcome Study (DATOS). It used structural equation modeling to describe factors…
Descriptors: Psychology, Motivation, Females, Structural Equation Models
Beauducel, Andre; Wittmann, Werner W. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
Fit indexes were compared with respect to a specific type of model misspecification. Simple structure was violated with some secondary loadings that were present in the true models that were not specified in the estimated models. The c2 test, Comparative Fit Index, Goodness-of-Fit Index, Incremental Fit Index, Nonnormed Fit Index, root mean…
Descriptors: Comparative Analysis, Personality Traits, Simulation, Goodness of Fit
Dolan, Conor V.; Schmittmann, Verena D.; Lubke, Gitta H.; Neale, Michael C. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
A linear latent growth curve mixture model is presented which includes switching between growth curves. Switching is accommodated by means of a Markov transition model. The model is formulated with switching as a highly constrained multivariate mixture model and is fitted using the freely available Mx program. The model is illustrated by analyzing…
Descriptors: Drinking, Adolescents, Evaluation Methods, Structural Equation Models
Raykov, Tenko – Structural Equation Modeling: A Multidisciplinary Journal, 2005
A bias-corrected estimator of noncentrality parameters of covariance structure models is discussed. The approach represents an application of the bootstrap methodology for purposes of bias correction, and utilizes the relation between average of resample conventional noncentrality parameter estimates and their sample counterpart. The…
Descriptors: Computation, Goodness of Fit, Test Bias, Statistical Analysis
Loken, Eric – Structural Equation Modeling: A Multidisciplinary Journal, 2005
The choice of constraints used to identify a simple factor model can affect the shape of the likelihood. Specifically, under some nonzero constraints, standard errors may be inestimable even at the maximum likelihood estimate (MLE). For a broader class of nonzero constraints, symmetric normal approximations to the modal region may not be…
Descriptors: Inferences, Computation, Structural Equation Models, Factor Analysis
Peer reviewedHayes, Steven C.; Strosahl, Kirk; Wilson, Kelly G.; Bissett, Richard T.; Pistorello, Jacqueline; Toarmino, Dosheen; Polusny, Melissa A.; Dykstra, Thane A.; Batten, Sonja V.; Bergan, John; Stewart, Sherry H.; Zvolensky, Michael J.; Eifert, Georg H.; Bond, Frank W.; Forsyth, John P.; Karekla, Maria; Mccurry, Susan M. – Psychological Record, 2004
The present study describes the development of a short, general measure of experiential avoidance, based on a specific theoretical approach to this process. A theoretically driven iterative exploratory analysis using structural equation modeling on data from a clinical sample yielded a single factor comprising 9 items. A fully confirmatory factor…
Descriptors: Psychopathology, Structural Equation Models, Quality of Life, Factor Analysis
Hammen, Constance; Shih, Josephine H.; Brennan, Patricia A. – Journal of Consulting and Clinical Psychology, 2004
An interpersonal stress model of depression transmission was tested in a community sample of nearly 800 depressed and never-depressed women and their 15-year-old children. It was hypothesized that maternal depression (and depression in the maternal grandmother) contributed to chronic interpersonal stress in the mothers, affecting quality of…
Descriptors: Interpersonal Competence, Structural Equation Models, Depression (Psychology), Mothers
Wei, Meifen; Mallinckrodt, Brent; Russell, Daniel W.; Abraham, W. Todd – Journal of Counseling Psychology, 2004
This study examined maladaptive perfectionism (concern over mistakes, doubts about one's ability to accomplish tasks, and failure to meet high standards) as both a mediator and a moderator between adult attachment (anxiety and avoidance) and depressive mood (depression and hopelessness). Survey data were collected from 310 undergraduates and…
Descriptors: Structural Equation Models, Anxiety, Depression (Psychology), Attachment Behavior
Xie, Jun; Bentler, Peter M. – Structural Equation Modeling: A Multidisciplinary Journal, 2003
Covariance structure models are applied to gene expression data using a factor model, a path model, and their combination. The factor model is based on a few factors that capture most of the expression information. A common factor of a group of genes may represent a common protein factor for the transcript of the co-expressed genes, and hence, it…
Descriptors: Path Analysis, Genetics, Structural Equation Models, Factor Analysis
Peer reviewedNieboer, Anna; Lindenberg, Siegwart; Boomsma, Anne; Van Bruggen, Alinda C. – Social Indicators Research, 2005
What are the dimensions of well-being? That is, what universal goals need to be realized by individuals in order to enhance their well-being? Social production function (SPF) theory asserts that the universal goals affection, behavioral confirmation, status, comfort and stimulation are the relevant dimensions of subjective well-being. Realization…
Descriptors: Test Validity, Well Being, Evaluation Methods, Measurement Techniques
Thompson, Elaine Adams; Mazza, James J.; Herting, Jerald R.; Randell, Brooke P.; Eggert, Leona L. – Suicide and Life-Threatening Behavior, 2005
The purpose of this study was to explore the roles of anxiety, depression, and hopelessness as mediators between known risk factors and suicidal behaviors among 1,287 potential high school dropouts. As a step toward theory development, a model was tested that posited the relationships among these variables and their effects on suicidal behaviors.…
Descriptors: Females, Dropouts, Structural Equation Models, Risk
Ferrer, Emilio; Hamagami, Fumiaki; McArdle, John J. – Structural Equation Modeling, 2004
This article offers different examples of how to fit latent growth curve (LGC) models to longitudinal data using a variety of different software programs (i.e., LISREL, Mx, Mplus, AMOS, SAS). The article shows how the same model can be fitted using both structural equation modeling and multilevel software, with nearly identical results, even in…
Descriptors: Computer Software, Structural Equation Models, Longitudinal Studies, Data Analysis
Hox, Joop; Lensvelt-Mulders, Gerty – Structural Equation Modeling, 2004
This article describes a technique to analyze randomized response data using available structural equation modeling (SEM) software. The randomized response technique was developed to obtain estimates that are more valid when studying sensitive topics. The basic feature of all randomized response methods is that the data are deliberately…
Descriptors: Structural Equation Models, Item Response Theory, Evaluation Research, Evaluation Methods

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