Webinar Series: Modeling Individual and Group Outcomes: An Introduction to Mixed-Effects Models, October 2025
Abstract:
Behavior analysts frequently work with repeated-measures and single-case data, yet traditional approaches often rely on aggregating observations or visual inspection alone. This intermediate-level webinar introduces mixed-effects (multilevel) modeling as an analytic framework that preserves individual differences while estimating population-level effects. Attendees will build intuition about concepts underlying these models, learn the fundamentals of specifying and interpreting mixed-effects models, see examples applied to behavioral data, and understand how these models can help characterize both group and individual trends without requiring data aggregation. The session will demystify key concepts (e.g. distinguishing fixed vs. random effects) and compare mixed-effects analyses to visual inspection and simpler statistics. Attendees will learn when mixed models are appropriate and how to specify and interpret a basic model. The session emphasizes practical takeaways over mathematical derivations, and will provide attendees resources to begin learning about and implementing these techniques in their own work.
Learning Objectives:
At the conclusion of the presentation, participants will be able to:
- Define mixed-effects modeling and distinguish between fixed effects and random effects in an analysis.
- Identify data scenarios (e.g. repeated measures or hierarchical datasets) where mixed-effects models are an appropriate analytic approach.
- Explain how incorporating random effects in a model accounts for individual differences and addresses limitations of traditional analyses that rely on data aggregation.
Instruction Level: Intermediate
CE Available: BACB/IBAO
Date: Wednesday, October 22nd.
Time: 1:00 PM EST