Multilevel Models and Structural Equation Models:

Two Frameworks, One Foundation

This brief and complimentary workshop is intended for researchers with experience in MLM, SEM, or both who want to understand how these two analytic traditions relate to one another. Using growth curve modeling as a common ground, the session demonstrates that random effects in MLM and latent variables in SEM are formally equivalent while also clarifying the practical situations where each framework has a distinct edge.

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Instructor:
Aidan Wright, PhD (University of Michigan)

Workshop Format:
Two-Hour Self-Paced Workshop

Workshop Dates and Times:
April 15, 2026
(2:00pm - 4:00pm ET)

Video Availability:
Video will be available on April 16, 2026

Multilevel models (MLM; aka mixed effects or hierarchical linear models) and structural equation models (SEM) are often taught as distinct analytic traditions, but they share far more in common than most researchers realize. This webinar bridges the two frameworks by focusing on their most natural point of overlap: growth curve modeling. Attendees will learn how random effects in MLM and latent variables in SEM are formally equivalent representations of individual differences, and how this equivalence means that multilevel growth models and latent growth curve models can produce identical results under common specifications. Beyond this convergence, the webinar will clarify where the frameworks diverge in practice — situations where the flexibility of traditional MLM (e.g., handling irregular time spacing, complex nesting structures, or large numbers of time points) offers clear advantages, and situations where SEM-based growth models shine (e.g., measurement error correction, structured residual covariances, multivariate growth processes, and model fit evaluation). The session will close with a brief description of multilevel structural equation modeling (MSEM) as a framework that brings together the strengths of both traditions. Throughout, attendees will observe live demonstrations of model estimation and will receive annotated code and practice data in both Mplus and R.

Registration Options

MLM & SEM: Two Frameworks, One Foundation

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