2026-04: When Regression Isn’t Enough: Modeling Romantic Relationships Data

When Regression Isn’t Enough: Modeling Romantic Relationships Data
Regression is a core tool in data science, but it can break down when data are structured, such as repeated measures or when observations are nested within groups. In these cases, standard models can produce biased or misleading results.
In this talk, Kristina introduces hierarchical linear models (HLMs) as a practical solution to these challenges. Using real data from research on romantic relationships, she will demonstrate how she tested the research question: "which types of shared relationship experiences are associated with heightened satisfaction for different types of individuals?" The session will cover the benefits of HLMs, how they extend from regression, and how to interpret their results.
This talk is intended for those who want to deepen their understanding of HLMs, improve their interpretation of regression-based analyses, or simply want to hear about findings from recent relationship science.

Where: Platform Calgary, East Annex
When: Wednesday, April 29, at 5:30 PM
Schedule:
5:30 – Food and Networking
6:00 – Presentation and Discussion
7:30 – Wrap Up

Speaker Bio:
Kristina Schrage, MBA, PhD, is a Senior Research Analyst at SAIT and a former Postdoctoral Scholar and Course Instructor at York University. Her work focuses on designing studies and analyzing complex data using advanced statistical methods. Her academic research examined the factors associated with enhanced relationship quality amongst couples. In her current role at SAIT, she conducts program evaluations to support academic leadership in improving program quality and student outcomes in the labour market.