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Konold, Timothy; Sanders, Elizabeth A. – Measurement: Interdisciplinary Research and Perspectives, 2020
Measuring and understanding the nature of informant/rater effects and differences (Level 1) on a common trait when the target of measurement is at the organizational level (Level 2) involves a number of methodological considerations. Although previous research has discussed single-level latent variable applications of the correlated…
Descriptors: Hierarchical Linear Modeling, Multitrait Multimethod Techniques, Measurement, Models
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Konold, Timothy – Journal of Psychoeducational Assessment, 2018
School-level contextual factors have been found to influence reports of school climate. The purpose of the current study was to evaluate the extent to which these associations are related to the school climate traits being measured or the methods (i.e., informants) used to obtain them. Data from a multilevel multitrait-multimethod (MTMM) design in…
Descriptors: Hierarchical Linear Modeling, Multitrait Multimethod Techniques, Computation, Context Effect
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Konold, Timothy R.; Shukla, Kathan – Educational Assessment, 2017
The use of multiple informants is common in assessments that rely on the judgments of others. However, ratings obtained from different informants often vary as a function of their perspectives and roles in relation to the target of measurement, and causes unrelated to the trait being measured. We illustrate the usefulness of a latent variable…
Descriptors: Educational Environment, Multitrait Multimethod Techniques, Computation, Validity
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Dickinson, Emily R.; Adelson, Jill L. – Journal of Advanced Academics, 2016
Practitioners and researchers interested in understanding student achievement, its predictors, and how it relates to other student outcomes are likely unaware of how the source information about achievement may offer subtly different pictures. This study applies multitrait-multimethod (MTMM) confirmatory factor analysis (CFA) within a structural…
Descriptors: Student Evaluation, Academic Achievement, Factor Analysis, Multitrait Multimethod Techniques
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Street, Karin Elisabeth Sørlie; Malmberg, Lars-Erik; Stylianides, Gabriel J. – ZDM: The International Journal on Mathematics Education, 2017
Students' self-efficacy expectations (SEE) in mathematics are associated with their engagement and learning experiences. Going beyond previous operationalisations of SEE we propose a new instrument that takes into account not only "facet-specificity" (expectations related to particular competences or skills) and "strength"…
Descriptors: Self Efficacy, Mathematics Tests, Mathematics Achievement, Performance Based Assessment
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Goldring, Ellen; Cravens, Xiu; Porter, Andrew; Murphy, Joseph; Elliott, Steve – Journal of Educational Administration, 2015
Purpose: The purpose of this paper is to contribute to the ongoing dialog of whether and how instructional leadership is distinguished conceptually from general leadership notions, such as charisma, and to continue the ongoing psychometric research on the The Vanderbilt Assessment of Leadership in Education (VAL-ED) by examining its convergent and…
Descriptors: Test Validity, Instructional Leadership, Elementary Schools, Middle Schools
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Shujuan, Wang; Meihua, Qian; Jianxin, Zhang – Journal of Psychoeducational Assessment, 2009
This article examines the psychometric structure of the Anxiety Control Questionnaire (ACQ) in Chinese adolescents. With the data collected from 212 senior high school students (94 females, 110 males, 8 unknown), seven models are tested using confirmatory factor analyses in the framework of the multitrait-multimethod strategy. Results indicate…
Descriptors: Multitrait Multimethod Techniques, Factor Structure, Adolescents, Measures (Individuals)
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Marsh, Herbert W.; Nagengast, Benjamin; Morin, Alexandre J. S.; Parada, Roberto H.; Craven, Rhonda G.; Hamilton, Linda R. – Journal of Educational Psychology, 2011
Existing research posits multiple dimensions of bullying and victimization but has not identified well-differentiated facets of these constructs that meet standards of good measurement: goodness of fit, measurement invariance, lack of differential item functioning, and well-differentiated factors that are not so highly correlated as to detract…
Descriptors: Locus of Control, Test Bias, Bullying, Structural Equation Models