The Quantitative Methods Lab in the Department of Human Development is directed by Felix Thoemmes.
Our lab is interested in developing and exploring new quantitative tools to improve data analysis of social science research. We use statistical theory, simulation studies, and applied examples in our work. Particular research interests are the use of modern tools of causal inference, (e..g, propensity score models), problems of missing data, and advanced structural equation models, including mediation analysis.
We work with various different statistical programming languages including, R, Mplus, SPSS, SAS, and Stata.
The lab currently has several opportunities to become involved in research projects on quantitative methods. Projects include work on propensity score methods, missing data, and structural equation models. If you are a Cornell undergraduate or graduate student and are interested in getting involved in the lab, please contact Felix Thoemmes firstname.lastname@example.org