Estimated marginal means (EMMs)—sometimes called least-squares means—are a powerful way to interpret and visualize results from linear and mixed-effects models. Yet many researchers struggle to extract, understand, and plot them.
In this 60-minute hands-on tutorial, participants will learn how to compute, interpret, and visualize EMMs using only base R functions together with the emmeans, car, and lme4 packages. We will start with simple linear models and progress to mixed models with random effects, highlighting how to obtain EMMs, confidence intervals, pairwise contrasts, and publication-ready base R plots. The session emphasizes conceptual understanding and practical code you can adapt immediately to your own analyses.
Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
About the Instructor
Manolo Romero Escobar is a seasoned statistical consultant and psychometrician with a passion for helping researchers.
Throughout his career, Manolo has worked extensively as a research and statistical consultant. He has served a diverse range of clients including health researchers, educational institutions, and government agencies. With a focus on linear mixed effects modeling, latent variable modeling, and scale development, Manolo brings a wealth of knowledge and experience to every project he undertakes.
Manolo is also proficient in statistical programming languages such as R, SPSS, and Mplus, and has experience with Python and SQL. He is passionate about leveraging technology as an educational and training tool, and he continuously enhances his skills to stay at the forefront of his field.
He holds a B.A. and Licentiate degree in Psychology from Universidad del Valle de Guatemala and a M.A. in Psychology (Area: Developmental and Cognitive Processes) from York University.
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