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Assessing Multilevel Mediation and Confidence Intervals in the 2-2-1 Model with Plausible Values: Simulation and Recommendations

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Title: Assessing Multilevel Mediation and Confidence Intervals in the 2-2-1 Model with Plausible Values: Simulation and Recommendations
Language: English
Authors: Yue Li, Fan Jia
Source: Large-scale Assessments in Education. 2026 14.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 30
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Hierarchical Linear Modeling, Mediation Theory, Intervals, Structural Equation Models, Monte Carlo Methods, Sample Size, Statistical Analysis
DOI: 10.1186/s40536-026-00286-x
ISSN: 2196-0739
Abstract: Mediation analysis in large-scale assessments often involves a multilevel structure, where students are nested within classrooms or schools. In such a context, multilevel structural equation modeling (MSEM) provides a flexible framework for estimating and testing the mediation process. Plausible values (PVs), however, present unique challenges for mediation analysis in large-scale assessments, yet methodological guidance remains limited. In particular, standard pooling procedures complicate the inference of indirect effects, which relies on the construction of confidence intervals. To address these gaps, we conducted a Monte Carlo simulation study comparing three modeling methods (aggregation, two-step approach, and MSEM) and three confidence interval methods (delta, distribution of the product, and Monte Carlo) in the context of 2-2-1 mediation with PVs. We evaluated their performance in terms of relative bias, confidence interval coverage, and power across a range of realistic conditions. Simulation results suggest that the MSEM-Monte Carlo combination performs best when sample size requirements were met. An empirical example is also provided to illustrate the practical implementation of 2-2-1 mediation analysis with PVs.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1508194
Database: ERIC
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  Data: Mediation analysis in large-scale assessments often involves a multilevel structure, where students are nested within classrooms or schools. In such a context, multilevel structural equation modeling (MSEM) provides a flexible framework for estimating and testing the mediation process. Plausible values (PVs), however, present unique challenges for mediation analysis in large-scale assessments, yet methodological guidance remains limited. In particular, standard pooling procedures complicate the inference of indirect effects, which relies on the construction of confidence intervals. To address these gaps, we conducted a Monte Carlo simulation study comparing three modeling methods (aggregation, two-step approach, and MSEM) and three confidence interval methods (delta, distribution of the product, and Monte Carlo) in the context of 2-2-1 mediation with PVs. We evaluated their performance in terms of relative bias, confidence interval coverage, and power across a range of realistic conditions. Simulation results suggest that the MSEM-Monte Carlo combination performs best when sample size requirements were met. An empirical example is also provided to illustrate the practical implementation of 2-2-1 mediation analysis with PVs.
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