Jason Rights
Meet Dr. Jason Rights, the Department of Psychology’s newest faculty member. Rights joined the department as Assistant Professor in the Quantitative Methods area on July 1 of this year.
Quantitative Methods is the study of research methods and techniques used to analyze and collect data. It covers a spectrum of topics ranging from mathematical psychology to the theory and techniques of mental measurement, individual differences, statistics, and data analysis.
Dr. Rights developed an interest in this area of research as an undergraduate student. Using a dataset of pairs of close friends, he learned how to use multilevel modeling (using random effects to model the variation between groups) to accommodate the multilevel structure (individuals nested within friendships). This was a fun experience for him and after that, he was hooked.
In his own words, Dr. Rights shares his background, research, and what he does for fun—outside of his research.
First of all, can you tell us a little about yourself?
I grew up in a small town in North Carolina. For my undergraduate studies, I stayed close to home and went to the University of North Carolina at Chapel Hill, where I studied psychology and math. I then got my Masters and Ph.D. in quantitative psychology at Vanderbilt. Vancouver is a bit of a change from the American South, but I’m thrilled to be making a home here.
“I try to answer the question: how can we improve statistical and methodological practice in psychological research?”
What kinds of questions do you try to answer through your research?
In a broad sense, I try to answer the question: how can we improve statistical and methodological practice in psychological research? More specifically, I focus on developing and evaluating methods for multilevel data contexts. An example of this would be a dataset with multiple observations collected over time from each person, with which a researcher could simultaneously investigate/model both within-person and between-person differences.
Can you give us an example of this in our daily lives?
The bulk of my research is methodological, and thus is not directly linked to any single real-life circumstance in particular. But in some general sense, multilevel structures are everywhere; for example, students are grouped into different schools, patients into different doctors/clinicians, and employees into different companies.
How did you become interested in this line of research?
I first became interested when completing my undergraduate honors thesis at UNC, where I worked with a dataset that involved pairs of close friends. I learned how to use multilevel modeling to accommodate the multilevel structure (individuals nested within friendships) and found it really useful and fun to learn. I also realized that such data structures were quite common in many different research areas, so I thought that studying multilevel modeling more generally would be a useful direction to take.
Can you tell us about any new research that you are particularly excited about?
I’ve recently been involved in some work on quantifying effect size for multilevel models, which I have found to be really fun. A lot of methods for computing effect size in single-level regression models don’t readily translate to multilevel contexts, and figuring out how to properly adapt or expand these methods has been exciting (and hopefully useful!).
Do you have a motto or favourite quote?
Tuum Est
What do you like to do in your free time?
In my free time, I like to swing dance, watch shows/movies, play video games, exercise, and listen to music. I also enjoy exploring cities and nature, and, in this regard, I’m so excited to see all that Vancouver and the surrounding area has to offer!
