Erica E. M. Moodie
Associate Professor, Biostatistics
Biostatistics Program Director
Department of Epidemiology, Biostatistics & Occupational Health
 McGill University

Purvis Hall, 1020 Pine Ave West, Montreal, QC H3A 1A2
first_name . last_name @ mcgill . ca

RESEARCH INTERESTS: Dynamic treatment regimes, causal inference,
longitudinal data, dose-response relationships, HIV.

...at McGill

BIOS 612:  Advanced Generalized Linear Models: Correlated Data (
Winter 2007, 2009, 2013; Fall 2010)
EPIB 659: Current Readings in Statistics (Winter 2008)
EPIB 607: Principles of Inferential Statistics in Medicine (Fall 2007, 2008, 2010, 2012)
...short courses:
Longitudinal data methods (March, 2014; Imperial College London Department of Mathematics)
Dynamic Treatment Regimes, Sequentially Randomized Trials, and Causal Inference

2006     Ph.D., Biostatistics, University of Washington.  
                   Thesis: Inference for optimal dynamic treatment regimes.
2004     M.Sc., Biostatistics, University of Washington.
2001      M.Phil., Epidemiology, University of Cambridge, UK.
                       Thesis: Modelling techniques for missing data: Intensive case-management versus standard
                       case-management for severe  psychosis.
2000     B.A. Mathematics and Statistics, University of Winnipeg.

FrontCover Chakraborty B. and Moodie E. E. M. (2013)

Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine.

Springer (Statistics for Biology and Health series).

Xiao Y., Abrahamowicz M., Moodie E. E. M., Weber R., and Young J. (2014) Flexible marginal structural models for estimating the cumulative effect of a time-dependent treatment on the hazard: Reassessing the cardiovascular risks of didanosine treatment in the Swiss HIV Cohort. Journal of the American Statistical Association (in press)

Moodie E. E. M., Stephens D. A. and Klein M. B. (2014) A marginal structural model for multiple-outcome data. Statistics in Medicine (in press)

Rich B., Moodie E. E. M., Stephens D. A. (2014) Simulating sequential multiple assignment randomized trials to generate optimal personalized Warfarin dosing strategies. Clinical Trials (in press)

Moodie E.E.M., Dean N., and Sun Y. R. (2013) Q-learning: Flexible learning about useful utilities. Statistics in Biosciences, doi: 10.1007/s12561-013-9103-z

Moodie E.E.M. and Chakraborty B. (2012) Q-learning for estimating optimal dynamic treatment rules from observational data. Canadian Journal of Statistics, 40: 629-645.

Shortreed S.M. and Moodie E.E.M.
(2012) Estimating the optimal dynamic treatment regime for schizophrenia:
Evidence from the sequentially randomized CATIE Schizophrenia Study. Journal of the Royal Statistical Society, Series C.

Moodie E.E.M. and Richardson T.S. (2010)  Estimating optimal dynamic regimes: Correcting bias under the null. The Scandinavian Journal of Statistics, 37: 126-146.

Moodie E. E. M.
(2009) A note on the variance of doubly-robust g-estimates. Biometrika, 96: 998-1004. 

Moodie E.E.M., Richardson T.S., and Stephens D.A. (2007) Demystifying optimal dynamic treatment regimes. Biometrics, 63(2): 447-455. 

Associate Editor, Biometrics
Associate Editor, JASA - Theory & Methods
Member, STRATOS (STRengthening Analytical Thinking for Observational Studies), Causal Inference topic group


Causal Inference in Statistics and the Quantitative Sciences Workshop at the Banff International Research Station (BIRS), 3-8 May, 2009
Proceedings of the BIRS Workshop: Special Issue of the International Journal of Biostatistics
Statistical Methods for HIV Research Workshop, 14-15 April, 2011
Causal Inference in Health Research Workshop, 9-13 May, 2011
Proceedings of the CRM Workshop: Special Issue of the International Journal of Biostatistics


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