[Mobilizeplans-starstudents] Mobilize Center Seminar, Alejandro Schuler, Dec 7

Mon Dec 4 08:24:53 PST 2017

Our next Mobilize Center Seminar is scheduled for Thursday, December 7th, and features Alejandro Schuler, PhD candidate in the Biomedical Informatics program at Stanford. He will be presenting “Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset”.

The Mobilize Center seminars are held once a month.  Please check Mobilize Events<http://mobilize.stanford.edu/events/> for updates.

We look forward to seeing you in December and at future seminars!

TITLE:
Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset

WHEN:
Thursday, December 7
noon - 1 pm

WHERE:
Y2E2 300, Stanford University

Abstract:
Many decisions in healthcare, business, and other policy domains are made without the support of rigorous evidence due to the cost and complexity of performing randomized experiments. Using observational data to answer causal questions is risky: subjects who receive different treatments also differ in other ways that affect outcomes. Many causal inference methods have been developed to mitigate these biases. However, there is no way to know which method might produce the best estimate of a treatment effect in a given study. In analogy to cross-validation, which estimates the prediction error of predictive models applied to a given dataset, we propose synth-validation, a procedure that estimates the estimation error of causal inference methods applied to a given dataset. In synth-validation, we use the observed data to estimate generative distributions with known treatment effects. We apply each causal inference method to datasets sampled from these distributions and compare the effect estimates with the known effects to estimate error. Using simulations, we show that using synth-validation to select a causal inference method for each study lowers the expected estimation error relative to consistently using any single method.

Bio:
Alejandro Schuler is a PhD candidate in the Biomedical Informatics program at Stanford. He researches the intersection of machine learning and causal inference with applications to healthcare informatics. He holds BS and MS degrees in mechanical engineering from UC Berkeley and UCLA, respectively. Apart from his research, Alejandro is the lead course designer for BIOMEDIN 215, Data-Driven Medicine. He is also an active participant in student government and activism, serving on the Graduate Student Council and in numerous roles across university committees, community centers, and student organizations.
To keep up-to-date on upcoming speakers and the dates, visit Mobilize Events<http://mobilize.stanford.edu/events/>.
Diane Bush
Assistant to Professor Scott Delp
NMBL, Mobilize Center, OpenSim
Stanford University
dbush1 at stanford.edu<mailto:dbush1 at stanford.edu>

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