About the Project

Our work seeks to develop, apply, and disseminate a Bayesian alternative to the frequentist (classical) statistical paradigm used in rigorous empirical research in the education sciences. We investigate Bayesian approaches motivated by problems in large-scale observational and longitudinal studies. Our past work, funded by IES, focused on developing Bayesian methods for propensity score analysis, missing data problems, and general issues of model uncertainty (Grant #R305D110001), as well as the development of Bayesian dynamic borrowing as a means of utilizing historical data in current analyses (Grant #R305D190053). Our current work funded by IES (Grant #R305D220012) focuses on developing Bayesian probabilistic models to forecast trends in education targets specified by the UN Sustainable Development Goals and utilizing international large-scale assessments.

This joint effort is housed within the Wisconsin Center for Education Research at the School of Education, University of Wisconsin-Madison.
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