THANK YOU FOR YOUR INTEREST IN THE WEBINAR. UNFORTUNATELY THE REGISTRATION IS CLOSED!
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norpen-2020@meds.ki.seNovember 11, 2020
14.00-14.50 An overview of G methods by Jessica Young*
14.50-15.00 10 minute break
15.00-16.00 Presentations from 5 junior researchers conducting studies on pharmacoepidemiology in Nordic data (TBA)
*This presentation is an introduction to G methods and teaser for the full NorPEN2021 pre-conference course on G-methods in relation to pharmacoepidemiology.
G-methods is a class of methods for estimating the causal effects of time-varying treatment strategies in longitudinal studies where time-varying confounders may be affected by past treatment. G-methods specifically aim to estimate Robins’s g-formula, a function of only measured study variables. Under assumptions that include no unmeasured confounding, the g-formula indexed by a particular time-varying treatment strategy equals the (counterfactual) outcome mean in the study population had all individuals adhered to that strategy. The g-formula is usually a high-dimensional function when the dimension of measured confounders is high and/or there are many follow-up times. Different g-methods (e.g. inverse probability weighting, parametric g-computation, targeted maximum likelihood estimation) constitute different estimation methods for this function of the longitudinal data. In this presentation, we will introduce counterfactual causal reasoning that motivates the g-formula as a target of statistical analysis and give a high-level overview of some different estimation methods.
Jessica Young, PhD
Assistant Professor and Biostatistician
Department of Population Medicine, Harvard Medical School
https://www.populationmedicine.org/JYoungHer research focuses on the development and application of statistical methods for estimating policy and clinically relevant causal effects of time-varying treatment strategies on health outcomes in the face of complex time-varying confounding and selection bias, competing events and treatments that are challenging to measure.
