Elizabeth A. Stuart, PhD
Center & Institute Affiliation(s):
- Drug Safety and Effectiveness, Center for
- Hopkins Population Center
- Prevention and Early Intervention, Center for
- Prevention of Youth Violence, Center for the
- Wendy Klag Center for Autism and Developmental Disabilities
624 N. Broadway
Hampton House 804
Baltimore , Maryland 21205
Personal website: http://www.biostat.jhsph.edu/~estuart/index.html
PhD , Harvard University , 2004
AM , Harvard University , 2001
Trained as a statistician, my primary research interests are in the development and use of methodology to better design and analyze the causal effects of public health and educational interventions. In this way I hope to bridge statistical advances and research practice, working with mental health and educational researchers to identify and solve methodological challenges.
I am particularly interested in the trade-offs in different designs for estimating causal effects, especially in terms of improving internal validity of non-experimental studies and external validity of randomized studies. This translates into two primary research areas. First, one of my primary research areas is in the use of propensity score methods for estimating causal effects in non-experimental studies (essentially as a tool to improve internal validity and reduce confounding). My interests in this area include providing advice for researchers in terms of best practice for estimation, diagnostics, and use of propensity score methods. This also includes investigation of how to handle complexities in propensity score methods, including multilevel data settings, covariate measurement error, and complex survey data.
My second primary research area is in methods to assess and enhance the external validity (generalizability) of randomized trial results and enable policymakers to determine how applicable the results of a particular randomized study are to their own target population. I also have interests in handling complexities in randomized experiments, in particular missing data and non-compliance.
The applied areas I focus on include autism, the long-term consequences of adolescent substance abuse, education, mental health services and systems, and the effects of health care reform models on mental health service use.
Honors and Awards
Fellow, American Statistical Association (2014)
JHSPH Golden Apple Award for Excellence in Teaching (2010)
JHSPH AMTRA Advising, Mentoring, and Teaching Recognition Award (2010, 2015)
Warren Miller Prize for best paper published in Volume 15 of Political Analysis, (Paper also selected as a “Fast Breaking Paper” by Thomson Reuters (2008)
JHSPH Edward R. Brewster Research Fund (Faculty Innovations Fund) Awardee (2007-2008)
National Science Foundation Graduate Research Fellowship (1999-2002)
Student paper award, American Statistical Association (2001)
Gertrude Cox award, American Statistical Association (2000)
William Cochran award in Statistics, Harvard University (1999)
Pokora Prize for Mathematics, Smith College (1997)
Phi Beta Kappa, Smith College (1997)
Magna cum laude, Smith College (1997)
Barry M. Goldwater Scholar (1995-1997)
Robert C. Byrd Scholar (1993-1997)
Bayesian modeling, biostatistics, causal inference, generalizability of results from randomized trials to target populations (external validity), measurement error, multi-level modeling, observational study, non-experimental study, prevention research, propensity scores
Erlangsen, A., …, Stuart, E.A., et al. (2014). Short and long term effects of psychosocial therapy provided to persons after deliberate self-harm: a register-based, nationwide multicentre study using propensity score matching. Lancet Psychiatry. Published online November 24, 2014.
Open access link: http://www.thelancet.com/journals/lanpsy/article/PIIS2215-0366(14)00083-2/fulltext
Stuart, E.A., Bradshaw, C.P., and Leaf, P.J. (2015). Assessing the generalizability of randomized trial results to target populations. Prevention Science 16(3): 475-485.
Stuart, E.A., Cole, S.R., Bradshaw, C.P., and Leaf, P.J. (2011). The use of propensity scores to assess the generalizability of results from randomized trials. The Journal of the Royal Statistical Society, Series A 174(2): 369-386. PMCID: 4051511. http://www.ncbi.nlm.nih.gov/pubmed/24926156.
Stuart, E.A. (2010). Matching Methods for Causal Inference: A review and a look forward. Statistical Science 25(1): 1-21. PMCID: PMC2943670. http://www.ncbi.nlm.nih.gov/pubmed/20871802.
Imai, K., King, G., and Stuart, E.A. (2008). Misunderstandings between experimentalists and observationalists about causal inference. Journal of the Royal Statistical Society, Series A 171: 481-502. http://onlinelibrary.wiley.com/doi/10.1111/j.1467-985X.2007.00527.x/full.
Selected publications highlighting methodological interests.