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Julia-Kim Walther; Martin Hecht; Steffen Zitzmann – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Small sample sizes pose a severe threat to convergence and accuracy of between-group level parameter estimates in multilevel structural equation modeling (SEM). However, in certain situations, such as pilot studies or when populations are inherently small, increasing samples sizes is not feasible. As a remedy, we propose a two-stage regularized…
Descriptors: Sample Size, Hierarchical Linear Modeling, Structural Equation Models, Matrices
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Sijia Huang; Dubravka Svetina Valdivia – Educational and Psychological Measurement, 2024
Identifying items with differential item functioning (DIF) in an assessment is a crucial step for achieving equitable measurement. One critical issue that has not been fully addressed with existing studies is how DIF items can be detected when data are multilevel. In the present study, we introduced a Lord's Wald X[superscript 2] test-based…
Descriptors: Item Analysis, Item Response Theory, Algorithms, Accuracy
Qinxin Shi; Jonathan E. Butner; Robyn Kilshaw; Ascher Munion; Pascal Deboeck; Yoonkyung Oh; Cynthia A. Berg – Grantee Submission, 2023
Developmental researchers commonly utilize longitudinal data to decompose reciprocal and dynamic associations between repeatedly measured constructs to better understand the temporal precedence between constructs. Although the cross-lagged panel model (CLPM) is commonly used in developmental research, it has been criticized for its potential to…
Descriptors: Models, Longitudinal Studies, Developmental Psychology, Behavior Problems
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Raykov, Tenko; DiStefano, Christine – Educational and Psychological Measurement, 2022
A latent variable modeling-based procedure is discussed that permits to readily point and interval estimate the design effect index in multilevel settings using widely circulated software. The method provides useful information about the relationship of important parameter standard errors when accounting for clustering effects relative to…
Descriptors: Hierarchical Linear Modeling, Correlation, Evaluation, Research Design
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French, Robert; Sariaslan, Amir; Larsson, Henrik; Kneale, Dylan; Leckie, George – Journal of Research on Educational Effectiveness, 2023
While the family is a critical determinant of educational achievement, methodological difficulties and the availability of data limit estimation of the family contribution in school effectiveness models. This study uses multilevel modeling to estimate the proportion of variation in student educational achievement between families, family-level…
Descriptors: Academic Achievement, Family Characteristics, Siblings, Family Structure
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Luo, Zhangjing; Lahat, Ayelet; Perlman, Michal; Howe, Nina; Recchia, Holly E.; Bukowski, William M.; Ross, Hildy – Merrill-Palmer Quarterly: Journal of Developmental Psychology, 2022
We examined the evolution of social pretend play in toddlers and tested whether children's age, gender, and language abilities were associated with changes in social pretend play over time. We employed a unique observational data set that followed 28 children (M[subscript age] = 27 months old; 57% boys) with each of two unfamiliar peers over 18…
Descriptors: Play, Fantasy, Toddlers, Language Skills
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Cao, Chunhua; Kim, Eun Sook; Chen, Yi-Hsin; Ferron, John – Educational and Psychological Measurement, 2021
This study examined the impact of omitting covariates interaction effect on parameter estimates in multilevel multiple-indicator multiple-cause models as well as the sensitivity of fit indices to model misspecification when the between-level, within-level, or cross-level interaction effect was left out in the models. The parameter estimates…
Descriptors: Goodness of Fit, Hierarchical Linear Modeling, Computation, Models
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Liu, Yixing; Levy, Roy; Yel, Nedim; Schulte, Ann C. – School Effectiveness and School Improvement, 2023
Although there is recognition that there may be differential outcomes for groups of students within schools, examination of outcomes for subgroups presents challenges to researchers and policymakers. It complicates analytic procedures, particularly when the number of students per school in the subgroup is small. We explored five alternatives for…
Descriptors: Growth Models, Hierarchical Linear Modeling, School Effectiveness, Academic Achievement
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Caniëls, Marjolein C. J.; de Jong, Jeroen P.; Sibbel, Hannes – Creativity Research Journal, 2022
In this study, we investigate how the level of work control predictability affects employee creativity. Specifically, we examine whether supervisor and coworker support moderate the predictability-creativity relationship. We use survey data from 128 employee--supervisor dyads from a governmental organization in Belgium. Multilevel analyses…
Descriptors: Correlation, Prediction, Comparative Analysis, Creativity
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Baek, Eunkyeng; Luo, Wen; Henri, Maria – Journal of Experimental Education, 2022
It is common to include multiple dependent variables (DVs) in single-case experimental design (SCED) meta-analyses. However, statistical issues associated with multiple DVs in the multilevel modeling approach (i.e., possible dependency of error, heterogeneous treatment effects, and heterogeneous error structures) have not been fully investigated.…
Descriptors: Meta Analysis, Hierarchical Linear Modeling, Comparative Analysis, Statistical Inference
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Hsu, Liwei; Chen, Yen-Jung – Asia-Pacific Education Researcher, 2023
The integration of technology in teachers' pedagogical practices has become the norm within various educational settings including the English as a Foreign Language (EFL) praxis. Although the technology, pedagogy, and content knowledge (TPACK) of EFL teachers has been explored previously, the contextual effects of the diffusion of technology at…
Descriptors: Technology Integration, Technological Literacy, Pedagogical Content Knowledge, English (Second Language)
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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
Moeyaert, Mariola – Behavioral Disorders, 2019
Multilevel meta-analysis is an innovative synthesis technique used for the quantitative integration of effect size estimates across participants and across studies. The quantitative summary allows for objective, evidence-based, and informed decisions in research, practice, and policy. Based on previous methodological work, the technique results in…
Descriptors: Meta Analysis, Evidence, Correlation, Predictor Variables
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Qian, Quan; Lau, Kit-ling – Journal of Research in Reading, 2022
Background: Research has shown that achievement goals and reading instruction play important roles in students' reading performance. However, little is known about the specific effects of different types of achievement goals and reading instructional practices on reading performance in mainland China. Methods: This study used Programme of…
Descriptors: Achievement Gains, School Districts, Teaching Methods, Reading Achievement
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Raykov, Tenko; Marcoulides, George A.; Akaeze, Hope O. – Educational and Psychological Measurement, 2017
This note is concerned with examining the relationship between within-group and between-group variances in two-level nested designs. A latent variable modeling approach is outlined that permits point and interval estimation of their ratio and allows their comparison in a multilevel study. The procedure can also be used to test various hypotheses…
Descriptors: Comparative Analysis, Models, Statistical Analysis, Hierarchical Linear Modeling
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