Sharpen your skills with expert instructors to gain an edge in current biostatistical and epidemiological methodology.

Dr. Atul Sharma is a pediatric nephrologist and biostatistician, who recently joined the Biostatistical Consulting Group as a senior consultant. As such, he brings a unique combination of clinical and statistical insights to statistical topics of interest to clinical investigators.

Dr. Atul Sharma | Propensity Scores: Making Sense of Non-Randomized Observational Data

Download Workshop Files Here Workshop preparation info Intro to R

Background: Randomized, controlled trials remain the gold standard in medical research. Nevertheless, with the increasing availability of administrative data and ‘natural experiments’ in health policy, clinical investigators must be prepared to interpret and analyze observational data arising from non-randomized trials and quasi-experimental study designs. This workshop is intended to support investigators as they design and interpret such trials. In it, we will focus on the application of propensity score methods to account for the selection biases that can confound such studies, even making it possible to analyze observational data as if they arose from a randomized trial.

Divided into two sessions, the first will provide a 1h introduction to the theory and application of propensity score methods, concentrating on real-world examples from the medical literature. The second session will be a 1h computer lab, to review the use of specialized software needed to perform propensity score analysis, including the R statistical language and specialized libraries for propensity score matching, assessment of post-match balance, and sensitivity analysis (e.g. the Matching and rbounds packages).

    • Understand the role of randomization in ensuring ‘covariate balance’ between experimental groups
    • Recognize the implications of selection biases as confounders in non-randomized observational data
    • Understand how the ‘balancing property’ makes it possible to condition on propensity scores to balance experimental groups in non-randomized trials

      Understand the various ways that of propensity scores (PS) can be used to analyze quasi-experimental designs, including:
    • Stratification
    • Regression adjustment
    • Weighted regression
    • Propensity score matching

      Recognize the limitations of propensity score methods and understand the importance of post-analysis assessment of modeling assumptions, including:
    • Appropriate methods for assessing covariate balance
    • Sensitivity analysis to test the robustness of conclusions to hidden biases from unobserved confounders (Rosenbaum bounds)
    • Devices for testing the robustness of study conclusions, including multiple control groups, coherence, and dose-response relationships.

Dr. Nathan Nickel is a Research Scientist at the Manitoba Centre for Health Policy and teaches Principles of Epidemiology in the department of Community Health Sciences at the University of Manitoba. Dr. Nickel’s expertise focuses on health service research using administrative data and health equity research in the area of maternal and child health. He is particularly interested in causal inference with respect to the evaluation of maternal and child health interventions.

Dr. Nathan Nickel | Don’t leave them behind: Epidemiology of Health Equity

Many health outcomes follow a social gradient where lower socioeconomic status is associated with worse health; health inequities are those systematic differences in health that are avoidable, remediable, and unfair. The 62nd World Health Assembly called upon the international population health community to monitor progress in in reducing health inequities. This workshop will focus equipping students with epidemiological measures often used in health equity research.

Students will have the opportunity to participate in an interactive workshop designed to familiarize them with key concepts in health equity. The workshop will provide an overview of the language of and theoretical considerations for health equity research. Participants will gain hands-on experience with a variety of epidemiological measures of health equity. Through these interactive exercises, students will gain an appreciation for the strengths and weaknesses of a variety of health equity measures.

    Learning Objectives:
    • Explain to a lay person the language used in health equity research and differentiate between terms such as “health inequity,” “health inequality,” and “health disparity.”
    • Interpret results from health equity research.
    • Describe why relative and absolute comparison measures can give different – and sometimes contradictory – impressions vis-à-vis changes in health disparities over time.
    • Explain how the size of population sub-groups can impact measures of health equality to other population health professionals.
    • Explain how the prevalence of the health indicator can impact equality measures.
    • Describe and apply a variety of health equality measures as well as their strengths and weaknesses.

Dr. Dan Chateau | Structural Equation Modeling Using SAS

The CALIS procedure in SAS/STAT is a general structural equation modeling (SEM) tool. This workshop introduces the general methodology of SEM and the applications of the CALIS procedure, with examples in social, educational, behavioral, and marketing research. Specifically, the following how‐to techniques of the CALIS procedure (SAS/STAT 13.2) are covered: (1) Specifying structural equation models with latent variables by using the PATH modeling language; (2) Interpreting the model fit statistics and estimation results; (3) Analyzing direct and indirect effects; (4) Modifying structural equation models. This workshop is designed for statisticians and data analysts who want to overview the applications of the SEM by the CALIS procedure. Attendees should have a basic understanding of regression analysis and experience using the SAS language. Previous exposure to SEM is useful, but not required.

Dan Chateau is a Research Scientist at the Manitoba Centre for Health Policy and an Assistant Professor in the Department of Community Health Sciences at University of Manitoba. He completed a PhD in Cognitive Psychology at the University of Western Ontario, and has conducted research at both MCHP, and as a consultant in the Biostatistics Consulting Unit in the College of Medicine, Faculty of Health Sciences. These positions provided a strong base in health services research and quantitative research methods. Dr. Chateau has worked on a broad range of projects for organizations as diverse as the WRHA, Manitoba Health, the Canadian Science Centre for Human and Animal Health, and the Division Scolaire Franco-Manitobaine, and with numerous clinicians and members of other departments at the University of Manitoba and beyond. In addition to contributing to major reports at MCHP, at present Dan is a member of the steering committee and quantitative methods team for the Canadian Network of Observational Drugs Effect Studies (CNODES), and a co-PI on a large multi-year grant investigating the effects of policies and interventions on health equity in Manitoba’s children (PATHS).

Career Development Panel

Panelist Bio
Mark Oremus Mark Oremus is an associate professor in the School of Public Health and Health Systems at the University of Waterloo. He is the Vice President of the Canadian Society for Epidemiology and Biostatistics (President effective June 2016) and the Communications Officer for the International Joint Policy Committee of the Societies of Epidemiology. Mark is an associate researcher at the Gilbrea Centre for Studies in Aging and an associate professor (part-time) in the Department of Clinical Epidemiology and Biostatistics at McMaster University. His research interests include aging, chronic disease, dementia, caregiving, health economics, quality-of-life, systematic reviews, public policy, and population health. Mark teaches epidemiologic methods at the undergraduate and graduate levels.
Dr. Al Artaman Dr. Al Artaman is a medical scientist with years of ex perience in clinical and pharmaco- epidemiology as well as public and global health epidemiology. As the Director of Epidemiology at Cancer Care Manitoba, he is responsibl e for cancer epidemiologic research management and collaboration with regional and national cancer research networks. He had previously worked as consultant in the private sector, resea rcher in the academia, and epidemiology manager in the government sector. He was recen tly the Coordination Committee chair of the Canadian Alliance for Regional Risk Factor Sur veillance. He is currently an expert for the Global Burden of Diseases, Injuries, and Risk Facto rs Study coordinated through the University of Washington.
Llwellyn Armstrong Llwellyn Armstrong is the statistician for the Institute for Wetland and Waterfowl Research within Ducks Unlimited Canada. She consults with research and field staff on issues of study design, sampling methodology, and statistical analyses and also conducts research into the use of innovative biostatistical techniques. She obtained her MSc in Statistics from the University of Manitoba and for six years she was the primary consultant for the Statistical Advisory Service at the Universit y of Manitoba. Llwellyn is a member of the Statistical Society of Canada, and has served as Regional Representative for Manitoba- Saskatchewan-NWT-Nunavut (2012-2015), Chair of the Strategic Planning Committee (2012- 2014), and currently serves as Executive Secretary (2015 – 2018).
Stephanie Sproule Stephanie Sproule, B.Sc. (hons), MMath is a Biostatistician with over 14 years of experience, primarily in the pharmaceutical industry. She holds a Bachelor of Science with honors in Statistics from the University of Manitoba, as well as a Masters of Mathematics in Statistics - Biostatistics from the University of Waterloo. Stephanie began her career in Saskatoon as a research officer with the Population Health Surveillance Unit of Saskatoon District Health, studying preventable injuries in children and infant mortality. She then moved back home to Winnipeg to take on the role of Biostatistician with Cangene Corporation (now Emergent BioSolutions). During her tenure at Cangene, Stephanie was responsible for the design and reporting of clinical trials at all phases of clinical development, including product development and manufacturing statistical support, and was eventually promoted to the management team where she gained a new insight into the worlds of clinical operations, outsourcing, budgeting and human resources. Currently, she is an independent consulting Biostatistician and founder of Optimum Statistics Inc., with clients ranging from PhD candidates to large global pharmaceutical companies. Stephanie lives in a small community outside Winnipeg with her husband and two young children. When she isn’t working, she can typically be found shuttling her children to and from sports activities or planning her next escape to a warmer climate!