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Romero, Lisa S.; Mitchell, Douglas E. – Educational Administration Quarterly, 2018
Purpose: Trust is a key component of successful schools. Although scholars widely agree that trust is multifaceted, there is less agreement about the number and nature of these factors. In the October 2016 issue of "Educational Administration Quarterly," C. M. Adams and Miskell (see EJ1112413) argued that their Teacher Trust of District…
Descriptors: Trust (Psychology), Teacher Administrator Relationship, Measures (Individuals), Teacher Surveys
Stapleton, Laura M.; McNeish, Daniel M.; Yang, Ji Seung – Educational Psychologist, 2016
Multilevel models are often used to evaluate hypotheses about relations among constructs when data are nested within clusters (Raudenbush & Bryk, 2002), although alternative approaches are available when analyzing nested data (Binder & Roberts, 2003; Sterba, 2009). The overarching goal of this article is to suggest when it is appropriate…
Descriptors: Hierarchical Linear Modeling, Data Analysis, Statistical Data, Multivariate Analysis
Garnier-Villarreal, Mauricio; Rhemtulla, Mijke; Little, Todd D. – International Journal of Behavioral Development, 2014
We examine longitudinal extensions of the two-method measurement design, which uses planned missingness to optimize cost-efficiency and validity of hard-to-measure constructs. These designs use a combination of two measures: a "gold standard" that is highly valid but expensive to administer, and an inexpensive (e.g., survey-based)…
Descriptors: Longitudinal Studies, Data Analysis, Error of Measurement, Research Problems
Canivez, Gary L.; Kush, Joseph C. – Journal of Psychoeducational Assessment, 2013
Weiss, Keith, Zhu, and Chen (2013a) and Weiss, Keith, Zhu, and Chen (2013b), this issue, report examinations of the factor structure of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV), respectively; comparing Wechsler Hierarchical Model (W-HM) and…
Descriptors: Intelligence Tests, Factor Structure, Comparative Analysis, Arithmetic
Valerio, Wendy H.; Reynolds, Alison M.; Morgan, Grant B.; McNair, Anne A. – Journal of Research in Music Education, 2012
The purpose of this research was to investigate the construct validity of the Children's Music-Related Behavior Questionnaire (CMRBQ), an instrument designed for parents to document music-related behaviors about their children and themselves. The research problem was to examine the hypothesized factorial structure of the questionnaire. From a…
Descriptors: Questionnaires, Construct Validity, Parents, Young Children
Martin, Andrew J.; Yu, Kai; Papworth, Brad; Ginns, Paul; Collie, Rebecca J. – Journal of Psychoeducational Assessment, 2015
This study explored motivation and engagement among North American (the United States and Canada; n = 1,540), U.K. (n = 1,558), Australian (n = 2,283), and Chinese (n = 3,753) secondary school students. Motivation and engagement were assessed via students' responses to the Motivation and Engagement Scale-High School (MES-HS). Confirmatory factor…
Descriptors: Foreign Countries, Motivation, Learner Engagement, Secondary School Students
Victor Snipes Swaim – ProQuest LLC, 2009
Numerous procedures have been suggested for determining the number of factors to retain in factor analysis. However, previous studies have focused on comparing methods using normal data sets. This study had two phases. The first phase explored the Kaiser method, Scree test, Bartlett's chi-square test, Minimum Average Partial (1976&2000),…
Descriptors: Factor Analysis, Factor Structure, Maximum Likelihood Statistics, Evaluation Methods

Veldman, Donald J. – Multivariate Behavioral Research, 1974
Descriptors: Factor Analysis, Factor Structure, Orthogonal Rotation, Research Problems

Prediger, Dale J. – Journal of Counseling Psychology, 1984
Focuses on anomalies in the O'Neil (1980) data on the factor structure of the Career Factor Checklist. Charges that critical errors compromise the conclusions regarding CFC valididty, and notes errors in analyses based on CFC scores. (JAC)
Descriptors: Factor Structure, Position Papers, Research Problems, Test Validity

ten Berge, Jos M. F. – Multivariate Behavioral Research, 1996
H. F. Kaiser, S. Hunka, and J. Bianchini have presented a method (1971) to compare two matrices of factor loadings based on the same variables, but different groups of individuals. The optimal rotation involved is examined from a mathematical point of view, and the method is shown to be invalid. (SLD)
Descriptors: Comparative Analysis, Factor Structure, Groups, Matrices

Mulaik, Stanley A. – Psychometrika, 1976
Discusses Guttman's index of indeterminacy in light of alternative solutions which are equally likely to be correct and alternative solutions for the factor which are not equally likely to be chosen. Offers index which measures a different aspect of the same indeterminacy problem. (ROF)
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices

Dunlap, William P.; Cornwell, John M. – Multivariate Behavioral Research, 1994
The fundamental problems that ipsative measures impose for factor analysis are shown analytically. Normative and ipsative correlation matrices are used to show that the factor pattern induced by ipsativity will overwhelm any factor structure seen with normative factor analysis, making factor analysis not interpretable. (SLD)
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices

Sachar, Jane – Journal of Experimental Education, 1980
The partial correlation coefficient is derived analytically under exemplary factor patterns. In these patterns, variables are described as an additive composition of a set of orthogonal factors, including general, common, and specific factors. Viewed in this framework, it is evident that the partial correlation may yield spurious results.…
Descriptors: Correlation, Factor Analysis, Factor Structure, Mathematical Models

Balderjahn, Ingo – Psychometrika, 1988
The nonnormed fit index's dependence on sample size in covariance structure analysis is discussed. Contrary to K. A. Bollen (1986) (whose alternative index depends on sample size), it is shown that the mean of the nonnormed fit index is independent of sample size for true and almost true models. (Author/TJH)
Descriptors: Factor Structure, Goodness of Fit, Maximum Likelihood Statistics, Research Problems

Merenda, Peter F. – Measurement and Evaluation in Counseling and Development, 1997
Offers suggestions for proper procedures for authors to use--and some pitfalls to avoid--when writing studies using factor analysis methods. Discusses distinctions among different methods of analysis, the adequacy of factor structure, and other notes of caution. Encourages authors to ensure that their research is statistically sound. (RJM)
Descriptors: Data Interpretation, Factor Analysis, Factor Structure, Reliability