Dr. Elizabeth Stuart, Associate Professor, is a statistician specializing in statistical methods for estimating causal effects in public health and education. She received her PhD in Statistics from Harvard University in 2004 and worked as a Researcher at Mathematica Policy Research for 2 years before joining JHSPH in 2006. Her work has primarily looked at the use of propensity score methods to estimate causal effects in non-experimental studies. She has published numerous papers developing propensity score methods, assessing their performance, and communicating matching methods to non-statistical audiences (Ho et al., 2007, Stuart 2010), and is very interested in providing practical tools and guidance to assist researchers in their use of these methods, including managing a website providing links to propensity score software (http://www.biostat.jhsph.edu/~estuart/propensityscoresoftware.html, accessed approximately 800 times per month). She has given many invited talks and workshops on propensity score methods and teaches a very popular course on causal inference at JHSPH.
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