Hi everyone!
This week at the Applied Statistics Workshop we will be welcoming *Miguel
Hernan*, a Professor of Epidemiology at the Harvard School of Public
Health. He will be presenting work entitled *Comparative effectiveness of
dynamic treatment strategies: The renaissance of the parametric g-formula*.
Please find the abstract below and on the website
<http://projects.iq.harvard.edu/applied.stats.workshop-gov3009/presentations/miguel-hernan-harvard>
.
As usual, we will meet in CGIS Knafel Room 354 and lunch will be provided.
See you all there!
-- Anton
Title: Comparative effectiveness of dynamic treatment strategies: The
renaissance of the parametric g-formula
Abstract: Causal questions about the comparative effectiveness and safety
of health-related interventions are becoming increasingly complex. Decision
makers are now often interested in the comparison of interventions that are
sustained over time and that may be personalized according to the
individuals’ time-evolving characteristics. These dynamic treatment
strategies cannot be adequately studied by using conventional analytic
methods that were designed to compare “treatment” vs. “no treatment”. The
parametric g-formula was developed by Robins in 1986 with the explicit goal
of comparing generalized treatment strategies sustained over time. However,
despite its theoretical superiority over conventional methods, the
parametric g-formula was rarely used for the next 25 years. Rather, the
development of causal inference methods for longitudinal data with
time-varying treatments focused on semiparametric approaches. In recent
years, interest in the parametric g-formula is growing and the number of
its applications increasing. This talk will review the parametric
g-formula, the conditions for its applicability, its practical advantages
and disadvantages compared with semiparametric methods, and several real
world implementations for comparative effectiveness research.
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