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Chunhua Cao; Yan Wang; Eunsook Kim – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterogeneity at the within level, between level, or both levels. This tutorial focuses on explicating the model specification of multilevel FMM that considers…
Descriptors: Hierarchical Linear Modeling, Factor Analysis, Nonparametric Statistics, Statistical Analysis
Li, Wei; Konstantopoulos, Spyros – Educational and Psychological Measurement, 2023
Cluster randomized control trials often incorporate a longitudinal component where, for example, students are followed over time and student outcomes are measured repeatedly. Besides examining how intervention effects induce changes in outcomes, researchers are sometimes also interested in exploring whether intervention effects on outcomes are…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Longitudinal Studies, Hierarchical Linear Modeling
Li, Wei; Konstantopoulos, Spyros – Journal of Experimental Education, 2019
Education experiments frequently assign students to treatment or control conditions within schools. Longitudinal components added in these studies (e.g., students followed over time) allow researchers to assess treatment effects in average rates of change (e.g., linear or quadratic). We provide methods for a priori power analysis in three-level…
Descriptors: Research Design, Statistical Analysis, Sample Size, Effect Size
Humphrey, Stephen E., Ed.; LeBreton, James M., Ed. – APA Books, 2019
Organizational relationships are complex. Employees do their work as individuals, but also as members of larger teams. They exist within various social networks, both within and spanning organizations. Multilevel theory is at the core of the organizational sciences, and unpacking multilevel relationships is fundamental to the challenges faced…
Descriptors: Hierarchical Linear Modeling, Theories, Institutional Research, Social Networks
Matsueda, Ross L.; Drakulich, Kevin M. – Sociological Methods & Research, 2016
This article specifies a multilevel measurement model for survey response when data are nested. The model includes a test-retest model of reliability, a confirmatory factor model of inter-item reliability with item-specific bias effects, an individual-level model of the biasing effects due to respondent characteristics, and a neighborhood-level…
Descriptors: Hierarchical Linear Modeling, Measurement, Surveys, Reliability
Smith, Daniel M.; Walls, Theodore A. – Measurement in Physical Education and Exercise Science, 2016
In sport and exercise research, examining both within- and between-individual variation is crucial. The ability to investigate change both within competitive events and across a competitive season is a priority for many sport researchers. The aim of this article is to demonstrate an approach to analyzing intensive longitudinal data collected…
Descriptors: Hierarchical Linear Modeling, Comparative Analysis, Athletics, Exercise
Miratrix, Luke; Feller, Avi; Pillai, Natesh; Pati, Debdeep – Society for Research on Educational Effectiveness, 2016
Modeling the distribution of site level effects is an important problem, but it is also an incredibly difficult one. Current methods rely on distributional assumptions in multilevel models for estimation. There it is hoped that the partial pooling of site level estimates with overall estimates, designed to take into account individual variation as…
Descriptors: Probability, Models, Statistical Distributions, Bayesian Statistics
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
Gandhi, Allison Gruner; Ogut, Burhan; Stein, Laura; Bzura, Robin; Danielson, Louis – Grantee Submission, 2017
This study reports findings from studies examining potential read-aloud accommodations on standardized reading comprehension assessments for students with decoding difficulties. Three types of accommodations were evaluated: question stems and answer options read aloud; question stems, answer options, and proper nouns read aloud; and full…
Descriptors: Testing Accommodations, Reading Difficulties, Decoding (Reading), Reading Tests
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
Jak, Suzanne; Oort, Frans J.; Dolan, Conor V. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
We present a test for cluster bias, which can be used to detect violations of measurement invariance across clusters in 2-level data. We show how measurement invariance assumptions across clusters imply measurement invariance across levels in a 2-level factor model. Cluster bias is investigated by testing whether the within-level factor loadings…
Descriptors: Statistical Bias, Measurement, Structural Equation Models, Hierarchical Linear Modeling
Timmermans, Anneke C.; Snijders, Tom A. B.; Bosker, Roel J. – Educational and Psychological Measurement, 2013
In traditional studies on value-added indicators of educational effectiveness, students are usually treated as belonging to those schools where they took their final examination. However, in practice, students sometimes attend multiple schools and therefore it is questionable whether this assumption of belonging to the last school they attended…
Descriptors: School Effectiveness, Student Mobility, Elementary Schools, Secondary Schools
Cho, Sun-Joo; Cohen, Allan S.; Bottge, Brian – Grantee Submission, 2013
A multilevel latent transition analysis (LTA) with a mixture IRT measurement model (MixIRTM) is described for investigating the effectiveness of an intervention. The addition of a MixIRTM to the multilevel LTA permits consideration of both potential heterogeneity in students' response to instructional intervention as well as a methodology for…
Descriptors: Intervention, Item Response Theory, Statistical Analysis, Models