<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
</head>
<body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">
<div style="margin: 0in 0in 0.0001pt;" class=""><font face="Arial" class=""><font class="">Our Mobilize Center Seminar is scheduled for TODAY, Thursday, December 7th, and features
<span style="white-space: pre-wrap;" class=""><b style="font-style: italic;" class="">Alejandro Schuler</b>, PhD candidate in the Biomedical Informatics program at Stanford.</span></font><span class=""> He will be presenting
</span><font class="">“<b class="">Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset</b>”.</font></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font face="Arial" class=""><font class=""><br class="">
</font></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font face="Arial" class=""><font class="">
<div class="" style="font-family: Calibri; margin: 0in 0in 0.0001pt;"><font face="Arial" class=""><font class="">In addition to today’s seminar, we will have a special seminar on Monday, December 11, featuring <span class="" style="white-space: pre-wrap;"><span class="" style="white-space: normal;"><b class=""><i class="">Sharada
Prasanna Mohanty</i></b></span>, Ph.D. candidate in Biotechnology and Bioengineering at the EPFL.</span></font><span class=""> The presentation is titled </span><font class="">“<b class="">CrowdAI: an open data science challenge platform</b>”.</font></font></div>
<div class="" style="font-family: Calibri; margin: 0in 0in 0.0001pt;"><font class="" face="Arial"> </font></div>
</font></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class=""><span class=""><font class="" face="Arial">The Mobilize Center seminars are held once a month. Please check <a href="http://mobilize.stanford.edu/events/" class="">Mobilize Events</a> for updates.</font></span></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"><br class="">
</font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial">We look forward to seeing you in December and at future seminars!<o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"> <o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"><b class="">TITLE:</b> <o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><b class=""><font face="Arial" class="">Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset</font></b></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"><b class=""> </b></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"><b class="">WHEN:</b> <o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"><b class="">Thursday, December 7</b><o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"><b class="">noon - 1 pm</b> <o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"> <o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"><b class="">WHERE:</b> <o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"><b class=""><span style="color: rgb(251, 2, 7);" class="">Y2E2 300, Stanford University </span></b><o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"> <o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><font class="" face="Arial"><b class="">Abstract:</b><o:p class=""></o:p></font></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><span style="font-family: Arial;" class="">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.</span></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><span style="font-family: Arial;" class=""><br class="">
</span></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><span style="font-family: Arial;" class=""><b class="">Bio:</b></span></div>
<div style="margin: 0in 0in 0.0001pt;" class=""><span style="font-family: Arial;" class="">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. </span></div>
<div style="margin: 0in 0in 0.0001pt;" class="">
<p class="MsoNormal"><font face="Arial" class=""><font class="">To keep up-to-date on upcoming speakers and the dates, visit </font><a href="http://mobilize.stanford.edu/events/" class="">Mobilize Events</a><font class="">.</font></font></p>
</div>
<div style="margin: 0in 0in 0.0001pt;" class=""><span style="font-family: Arial;" class="">Diane Bush</span></div>
<div class="">
<div class=""><font face="Arial" class="">Assistant to Professor Scott Delp<br class="">
NMBL, Mobilize Center, OpenSim<br class="">
Stanford University<br class="">
<a href="mailto:dbush1@stanford.edu" class="">dbush1@stanford.edu</a><br class="">
</font></div>
</div>
<br class="">
</div>
</div>
</div>
<br class="">
</div>
</div>
<br class="">
</div>
.=.=.=.=.=.=.=.=.=.=.=.=.=.=.=.=.=.=.=.<br class="">
nmbl_core_members mailing list<br class="">
<a href="mailto:nmbl_core_members@lists.stanford.edu" class="">nmbl_core_members@lists.stanford.edu</a><br class="">
<a href="https://mailman.stanford.edu/mailman/listinfo/nmbl_core_members" class="">https://mailman.stanford.edu/mailman/listinfo/nmbl_core_members</a><br class="">
<br class="">
</div>
</div>
</div>
.=.=.=.=.=.=.=.=.=.=.=.=.=.=.=.=.=.=.=.<br class="">
nmbl_core_members mailing list<br class="">
<a href="mailto:nmbl_core_members@lists.stanford.edu" class="">nmbl_core_members@lists.stanford.edu</a><br class="">
<a href="https://mailman.stanford.edu/mailman/listinfo/nmbl_core_members" class="">https://mailman.stanford.edu/mailman/listinfo/nmbl_core_members</a><br class="">
<br class="">
</div>
</body>
</html>