Join us in person for a lecture by professor Yusuf Kara, PhD, on Tuesday, September the 8th, 2026 at the Newman Alumni Center. Talk Title: “Latent Variable Modeling in the Behavioral Sciences: Applications and Implications.”
Dr. Kara is an Assistant Professor of Research, Measurement, and Evaluation in the School of Education and Human Development at the University of Miami. He previously served as a Research Assistant Professor and Senior Data Analyst at Southern Methodist University’s Center on Research and Evaluation. His research centers on latent variable modeling, with particular emphasis on the development and applications of innovative data analytic techniques for educational and psychological measurement. He has collaborated with scholars across education, statistics, and computer science on federally funded projects aimed at advancing the assessment of oral reading fluency.
Register Now (free)
Tuesday, Sept. 8 • 4:00-6:00 PM
Newman Alumni Center, Toll Library, 6200 San Amaro Drive, Coral Gables FL 33146 | Map + Directions
Abstract: Latent variables are ubiquitous in quantitative research across the behavioral sciences, including education and psychology. They are commonly used to represent unobservable constructs such as mathematical ability, depression, and motivation. More broadly, latent variables provide a flexible framework for modeling a wide range of phenomena, including higher-level contextual effects (e.g., schools or classrooms), individual rates of change in longitudinal studies, and missing data processes.
In this talk, Dr. Kara will present research on the development and application of latent variable modeling approaches. He will begin with a brief, intuitive introduction illustrating how latent variables naturally arise in many quantitative research settings. He will then showcase several research projects that use both established and novel latent variable models to address substantive questions in educational and behavioral research, including the measurement of oral reading fluency, the estimation of early-years classroom effects, and the modeling of self- and interactive contingency in mother–infant dyads.
