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Jennrich, Robert I.; Bentler, Peter M. – Psychometrika, 2012
Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…
Descriptors: Factor Structure, Factor Analysis, Models, Comparative Analysis
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Furman, Wyndol; Buhrmester, Duane – International Journal of Behavioral Development, 2009
This paper describes an alternative version of the Network of Relationships Inventory, which was designed to assess how frequently different relationships were used to fulfill the functions of three behavioral systems: attachment, caregiving, and affiliation. Psychometric and validational evidence is presented including: (a) high internal…
Descriptors: Factor Structure, Adolescents, Psychometrics, Organizations (Groups)
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van der Sluis, Sophie; Dolan, Conor V.; Stoel, Reinoud D. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
This article is concerned with the seemingly simple problem of testing whether latent factors are perfectly correlated (i.e., statistically indistinct). In recent literature, researchers have used different approaches, which are not always correct or complete. We discuss the parameter constraints required to obtain such perfectly correlated latent…
Descriptors: Testing, Factor Structure, Structural Equation Models, Correlation
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Bentler, Peter M. – Structural Equation Modeling, 2000
Discusses issues related to model evaluation in structural equation modeling. Supports nested model comparisons via sequential chi-square difference tests as consistent with the four-step approach to model evaluation when models of the factor analytic simultaneous equation type are entertained. (Author/SLD)
Descriptors: Chi Square, Evaluation Methods, Factor Analysis, Factor Structure
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Prescott, David P. – Journal of Child Sexual Abuse, 2004
Clinicians and other professionals evaluating, managing, and treating sexually abusive youth are frequently called upon to offer judgments regarding risk for sexual reoffense. There are currently no empirically validated methods for accurately classifying risk among this population. Therefore, those faced with this task have an obligation to…
Descriptors: Sexual Abuse, Youth, Risk, Recidivism
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Cassidy, Deborah J.; Hestenes, Linda L.; Hegde, Archana; Hestenes, Stephen; Mims, Sharon – Early Childhood Research Quarterly, 2005
The purpose of the current study was to examine the psychometric properties of the Early Childhood Environment Rating Scale-Revised (ECERS-R) with a large sample (1313 classrooms). We explored both the seven subscales and the possibility of fewer distinct aspects of quality being measured by the scale. The large sample size allowed both…
Descriptors: Psychometrics, Factor Analysis, Factor Structure, Preschool Children
Dockrell, W. B. – 1987
With the advent of profiling and maintaining records of achievement, the assessment of the affective characteristics of pupils has become an issue of general concern in England. The Scottish Council for Research in Education has been involved in programs investigating the assessment of individuals and the evaluation of curricula. Teachers can…
Descriptors: Affective Behavior, Affective Measures, Elementary Secondary Education, Evaluation Criteria
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Furlong, Michael J.; Greif, Jennifer L.; Bates, Michael P.; Whipple, Angela D.; Jimenez, Terese C.; Morrison, Richard – Psychology in the Schools, 2005
Planning is essential to creating safe schools and it is required by the Federal No Child Left Behind legislation (U.S. Department of Education, 2004) and implemented via district local education action plans. The implementation of these plans involves continuous monitoring and reevaluation of information pertinent to each campus. As such, this…
Descriptors: Federal Legislation, Safety, Psychometrics, Factor Structure