Additional Appointments
Affiliate Faculty, Center for Statistics and the Social Sciences
Research Interests
Elizabeth Sanders
My teaching and research are focused on the appropriate use of quantitative methods in education and related disciplines. More specifically, my research interests center on analytic methods for nested data, including multilevel modeling (MLM), structural equation modeling/covariance analysis (SEM), and exponential random graph modeling (ERGM). In addition to my methodological work, I collaborate with a number of colleagues on a variety of educational, behavioral, and health research, with an emphasis on promoting equitable resource access for at-risk and historically underserved populations.
Please see Google scholar for an up-to-date list of peer-reviewed publications.
Graduate students
Note: I only accept Ph.D. students who have completed their master's degree in our Measurement & Statistics program. Each year I consider accepting 1-2 new master's students.
My Measurement & Statistics (M&S) graduate students study analytic methods in the context of educational research, typically by employing Monte Carlo simulation investigations using R, Mplus, or SAS. Reflecting the multidisciplinary history of quantitative research methods, our program's graduate students come from diverse academic and professional backgrounds, including economics, education, engineering, medicine, political science, psychology, sociology, and statistics, to name a few. Regardless of background, our M&S faculty and students share a common interest in studying analytic tools, and a common mission to improve education policy and equity through the study and practice of high-quality quantitative methodology.
All M&S graduate students are expected to take foundational coursework in education (e.g., learning theory, history of education) as well as a range of coursework in quantitative methods within and outside of the College of Education. Doctoral students are nearly always funded as TAs or RAs, and those who are accepted into the Ph.D. program are typically students who began in our master's program. Students who graduate with a master's from our program are employed by local district and state agencies, university research centers, and private companies (e.g., market research, software testing research, etc.). Students who graduate with a Ph.D. go on to work in academic appointments (teaching and research) or leadership roles within district and state agencies, university research centers, testing organizations, and private industry.
I am always interested in prospective students who demonstrate a passion for quantitative methods (as its own discipline), strong writing and analytic skills, and share our commitment to educational equity.
Courses
I regularly teach courses in applied measurement in education, basic educational statistics, experimental design, multilevel modeling, multiple regression, and network measurement and analysis. I have also taught classes in structural equation modeling and survey research. From time to time, I offer specialized seminars, such as psychology of math. All graduate courses include statistical computing in R.