Skip to main content

COVID-19 Research Resources
A curated list of research resources around guidelines, policies, and procedures related to COVID-1, drawn from Harvard University, affiliated academic healthcare centers, and government funding agencies

COVID-19 Research Resources
A curated list of research resources around guidelines, policies, and procedures related to COVID-1, drawn from Harvard University, affiliated academic healthcare centers, and government funding agencies

Calendar

Biostatistics short course: Precision Medicine – A Statistical Perspective on Estimating the Best Treatment Strategy – April 8

Friday, April 8, 2022
9:30 am – 1:00 pm
Online

Biostatistics short course: Precision Medicine – A Statistical Perspective on Estimating the Best Treatment Strategy

Evidence-based medicine relies on using data to provide recommendations for effective treatment decisions for individual patients. However, in many settings, effects may be heterogeneous across individuals or, in the case of treatments given sequentially over time, within the same individuals as their health evolves. Healthcare providers are faced with the daunting task of making sequential therapeutic decisions having seen few patients with a given clinical history. Adaptive treatment strategies (ATS) operationalize the sequential decision-making process in the precision medicine paradigm, offering statisticians principled estimation tools that can be used to incorporate patient’s characteristics into a clinical decision-making framework so as to adapt the type, dosage, or timing of intervention according to patients’ evolving needs.

This half-day course led by Erica Moodie, PhD, professor of biostatistics at McGill University, will provide an overview of precision medicine from the statistical perspective. Topics will include randomized trial designs for ATS, common estimation strategies for the single stage case (with a focus on applications to non-experimental data), and extensions of (some) estimation methods to the multi-stage setting. Some brief references to R will be made, but there are no hands-on components. Students unfamiliar with R will not be at a disadvantage. A basic knowledge of regression and some exposure to basic causal concepts (confounding, the propensity score) are assumed.

Speaker Bio:

Erica E. M. Moodie, PhD, is a professor of biostatistics at McGill University and a Canada research chair (Tier 1) in statistical methods for precision medicine. She additionally serves as an associate editor of biometrics and a statistical editor of the Journal of Infectious Diseases. Her main research interests are in causal inference and longitudinal data with a focus on precision medicine. Moodie is the 2020 recipient of the CRM-SSC Prize in Statistics and an elected member of the International Statistical Institute. She holds a Chercheur de Merite Career Award from the Fonds de Recherche du Quebec-Sante. Moodie obtained her MPhil in epidemiology in 2001 from the University of Cambridge and a PhD in Biostatistics in 2006 from the University of Washington. 

*Please note, registration ends April 6, 2022.

Sign up to receive our newsletter: courses, funding, events, and resources.