Special Seminar
John Jackson, PhD
Yerby Postdoctoral Research Fellow, Harvard School of Public Health
Confounding: I know it when I see it
ALL ARE WELCOME
Abstract:
The effects of joint exposures (or exposure regimes) include those of adhering to assigned treatment vs. placebo in a randomized controlled trial, duration of exposure in a cohort study, interactions between exposures, and direct effects of exposure, among others. Unlike the setting of a single point exposure (e.g. propensity score matching), there are few tools to describe confounding for joint exposures or how well a method resolves it. Starting from concepts of sequential exchangeability, I will outline covariate-balance diagnostics and data visualizations that can (1) describe time-varying confounding (2) assess whether covariates are predicted by prior exposures given their past, the indication for g-methods (3) describe residual confounding after inverse probability weighting.
Bio:
Dr. Jackson is an epidemiologist with interests that span mental health, pharmacoepidemiology, and health disparities. His primary focus is to develop and apply causal inference methods to understand the etiology of disparities in mental health treatment and their relation to disparities in long-term recovery, functioning, and co-morbidity. This program aims to provide evidence that can target further research and interventions to bring about equitable mental health.
Dr. Jackson also maintains an active research program on developing conceptually grounded diagnostic tools to help stakeholders assess the validity of epidemiologic and clinical studies. He has received pilot funding from Harvard Catalyst to extend and apply these methods to Sequential, Multiple Assignment, Randomized Trial (SMART) designs and placebo controlled trials in schizophrenia, in collaboration with the OPTICS project.
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