Propensity score methods for estimating causal effects in non-experimental studies

Tuesday, 14 November 2017
9.00 - 5.00
University of Melbourne
Redmond Barry Building, Latham Theatre Tin Alley, Building 115, Room 102
Carlton 3052

ViCBiostat is hosting respected speaker Professor Elizabeth Stuart from Johns Hopkins University who will present this one-day workshop.

Propensity scores are an increasingly common tool for estimating the effects of interventions in observational (“non-experimental”) settings and for answering complex questions in randomized controlled trials.  They can be of great use in medicine, public health, and the social sciences, for example examining the effects of long-term use of pharmaceuticals, or of depression treatment for adolescents, or of potentially adverse exposures such as childhood maltreatment.   This short course will discuss the importance of the careful design of observational studies, and the role of propensity scores in that design, with the main goal of providing practical guidance on the use of propensity scores to estimate causal effects.  The course will cover the primary ways of using propensity scores to adjust for confounders when estimating the effect of a particular “cause” or “intervention,” including weighting, subclassification, and matching. 

Topics covered will include:

- How to specify and estimate the propensity score model
- Selecting covariates to include in the modes
- Diagnostics
- Common challenges and solutions. 

The methods will be illustrated using a case study using large-scale administrative data from Denmark to estimate the effects of a suicide prevention program on suicide attempts.    Software for implementing analyses using propensity scores will be briefly discussed, including resources for Stata and R.   The course will also highlight recent advances in the propensity score literature,  including prognostic scores, covariate balancing propensity scores, methods for non-binary treatments (such as dosage levels of a drug or when comparing multiple programs simultaneously), and approaches to be used when there are large numbers of covariates available (as in claims or other “big” data). 

Who should attend?

Attendees will either be biostatisticians or will have completed “applied multivariable regression” subjects in an MPH/M.Epi/MSc.


University of Melbourne
Redmond Barry Building
Latham Theatre
Tin Alley
Building 115, Room 102
(see map attached)


There will be several demonstrations of implementing the methods discussed in both Stata and R, and example computing code will be provided to participants. There will, however, be no computing practical classes on the day, so there is no need for participants to bring a laptop computer.


Click here to see workshop fees.

Registration via Trybooking now open. 

Please note the following:

  • Early bird rate finishes on 16/10/17
  • Students must be full time.  ID number is required to register.
  • ViCBiostat post docs and PhD students only attend FREE but must complete online registration process for administration purposes. Refer to email from Marian for discount code instructions.
  • MCRI staff may request a cost centre transfer but must complete online registration process for administration purposes.  Please contact Marian Chandler for details regarding the process prior to registering.  
  • All prices inclusive of GST.
  • Registration fee includes catering.
  • A small booking fee applies in addition to prices stated.
  • Cancellation policy: refund of registration fee less 25% if cancellation within 1 week of course.

    Contact Marian Chandler for any questions regarding registration.


Prof. Elizabeth Stuart

Johns Hopkins Bloomberg School of Public Health

Elizabeth A. Stuart, Ph.D. is Professor in the Department of Mental Health at the Johns Hopkins Bloomberg School of Public Health, with joint appointments in the Department of Biostatistics and the Department of Health Policy and Management, and Associate Dean for Education at JHSPH. She received her Ph.D. in statistics in 2004 from Harvard University and is a Fellow of the American Statistical Association. Dr. Stuart has extensive experience in methods for estimating causal effects and dealing with the complications of missing data in experimental and non-experimental studies, particularly as applied to mental health, public policy, and education. She has published influential papers on propensity score methods and generalizing treatment effect estimate to target populations and taught courses and short courses on causal inference and propensity scores to a wide range of audiences, including at JHSPH (both in person and online), the US Food and Drug Administration, and at conferences.  Her primary areas of application include estimating the effects of health care interventions (such as an accountable care model) on mental health service utilization, treatments for children with autism spectrum disorders, and the evaluation of school-based preventive interventions.  She also has extensive experience with policy evaluation, through previous employment at Mathematica Policy Research, and co-directs the JHSPH Center for Mental Health and Addiction Policy Research.  Dr. Stuart has received research funding for her work from the National Institutes of Health, the US Institute of Education Sciences, and the National Science Foundation and has served on advisory panels for the National Academy of Sciences and the US Department of Education.  She is Methods Editor for the Journal of Research on Educational Effectiveness and serves as Chair of the Patient Centered Outcomes Research Institute's (PCORI's) inaugural Clinical Trials Advisory Panel.  Dr. Stuart was recently recognized with the mid-career award from the Health Policy Statistics Section of the American Statistical Association and the Gertrude Cox Award for applied statistics.  

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