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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
Buckley, Pamela; Moore, Brooke; Boardman, Alison G.; Arya, Diana J.; Maul, Andrew – American Educational Research Journal, 2017
K-12 intervention studies often include fidelity of implementation (FOI) as a mediating variable, though most do not report the validity of fidelity measures. This article discusses the critical need for validated FOI scales. To illustrate our point, we describe the development and validation of the Implementation Validity Checklist (IVC-R), an…
Descriptors: Intervention, Fidelity, Program Implementation, Test Validity
Kärner, Tobias; Sembill, Detlef; Aßmann, Christian; Friederichs, Edgar; Carstensen, Claus H. – Frontline Learning Research, 2017
The investigation of learning processes by assessing students' experience along with objective characteristics within a classroom context has a long tradition in empirical learning process research (e.g. Sembill, 1984 et passim; Wild & Krapp, 1996). However, most of the existing studies confine themselves to psychological variables that seem…
Descriptors: Longitudinal Studies, Stress Variables, Hierarchical Linear Modeling, Learning Processes
Schweig, Jonathan – Journal of Educational and Behavioral Statistics, 2014
Measures of classroom environments have become central to policy efforts that assess school and teacher quality. This has sparked a wide interest in using multilevel factor analysis to test measurement hypotheses about classroom-level variables. One approach partitions the total covariance matrix and tests models separately on the…
Descriptors: Factor Analysis, Robustness (Statistics), Measurement, Classroom Environment
Jeon, Minjeong – ProQuest LLC, 2012
Maximum likelihood (ML) estimation of generalized linear mixed models (GLMMs) is technically challenging because of the intractable likelihoods that involve high dimensional integrations over random effects. The problem is magnified when the random effects have a crossed design and thus the data cannot be reduced to small independent clusters. A…
Descriptors: Hierarchical Linear Modeling, Computation, Measurement, Maximum Likelihood Statistics