Dear all,
We have a very special visiting speaker tomorrow at Applied Stats. Cathy O'Neil earned a Ph.D. in math from Harvard, was postdoc at the MIT math department, and a professor at Barnard College where she published a number of research papers in arithmetic algebraic geometry. After switching to the private sector, Cathy worked as a quant for the hedge fund D.E. Shaw in the middle of the credit crisis, and then for RiskMetrics, a risk software company that assesses risk for the holdings of hedge funds and banks. For the last couple years she's been a data scientist in the New York start-up scene. She writes a blog at mathbabe.org<http://mathbabe.org> and is involved with the #Occupy Wall Street Alternative Banking Working Group.
Check out her recent interview with Russ Roberts on EconTalk here: http://www.econtalk.org/archives/2013/02/cathy_oneil_on.html
Abstract: In this talk I will discuss the common problems data nerds face when they work in industry. Those include problems that academic statisticians face, of course, but also extend to other kinds of communication and political problems. Moreover, considering the cultural effects of widespread mathematical modeling, the general inaccessibility of mathematical models from the point of the view of the public, and the general blind trust the average person has in mathematics, it's potentially a pretty big deal. Let's try to categorize the risks and start coming up with ways to address them through setting standards for modeling as well as through educating the public.
As per usual the talk starts at 12 noon in CGIS Knafel K354<http://map.harvard.edu/?bld=04471&level=9>. Lunch will be served.
I look forward to seeing of you tomorrow!
Tess
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Tess Wise
PhD Candidate
Harvard Department of Government
http://tesswise.com
Dear All --
Our speaker tomorrow at Applied Stats<http://projects.iq.harvard.edu/applied_stats> will be Teppei Yamamoto from MIT PoliSci. Professor Yamamoto's talk is titled "Identification and Estimation of Causal Mediation Effects with Treatment Noncompliance." As per usual, the talk will be held in CIGS K354<http://map.harvard.edu/?bld=04471&level=9> at 12 noon and lunch will be served. The abstract for Professor Yamamoto's talk can be found below and you can download the associated article from our website at: http://projects.iq.harvard.edu/applied_stats/event/teppei-yamamoto-mit.
Abstract:
Treatment noncompliance is a common problem in program evaluation. The problem is particularly severe when the analyst is interested in causal mediation effects. This is because, somewhat counterintuitively, the mediated portion of an intention-to-treat (ITT) effect cannot be nonparametrically identified even when treatment assignment is randomized and the ignorability of the observed mediator is assumed. This paper shows that, once the standard instrumental variables assumptions are made, the mediated ITT effects and the local average causal mediation effects (LACME) for compliers can in fact be identified under a local sequential ignorability assumption. The commonly-used naïve estimators for the mediated ITT effect and LACME are shown to be biased in unknown directions. The proposed estimators are illustrated via a simulation study and applied to data from a job training experiment. The proposed method, implemented in an open-source R package, enables researchers to investigate causal mechanisms by which the treatment affects the outcome of interest even when treatment noncompliance exists.
Tess
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Tess Wise
PhD Candidate
Harvard Department of Government
http://tesswise.com
Hi all --
It is my pleasure to announce that our next speaker at Applied Stats<http://projects.iq.harvard.edu/applied_stats> will be Arthur Spirling from the Harvard Department of Government. The workshop will be in CGIS K354<http://map.harvard.edu/?bld=04471&level=9> this Wednesday, October 16th at noon. As per usual, lunch will be served.
Professor Spirling's presentation will be on "Party Cohesion in Westminster Systems: Inducements, Replacement and Discipline in the House of Commons, 1836--1910." You can read the abstract and find the corresponding paper here: http://projects.iq.harvard.edu/applied_stats/event/arthur-spirling-governme…
I look forward to seeing you all tomorrow!
Tess
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Tess Wise
PhD Candidate
Harvard Department of Government
http://tesswise.com
Hi everyone!
I'm excited to announce that tomorrow at Applied Stats<http://projects.iq.harvard.edu/applied_stats> we will have Professor Cynthia Rudin from MIT.
Professor Rudin is an associate professor of statistics at MIT, and her talk will be on "Growing a Pattern From a Seed." The talk will describe two methods and applications for pattern detection, where patterns are grown from a seed of a few items:
1) Growing a List: The next generation of search engines should not simply retrieve URLs, but should aim at retrieving information. Professor Rudin and her collaborators have designed a system that leads into this next generation, leveraging information from across the Internet to grow an authoritative list on almost any topic, starting from a seed.
2) Crime Series Detection: In joint work with the Cambridge Police Department, Professor Rudin and her collaborators have designed a method called "Series Finder" that detects patterns of crime that are committed by the same individual or group. The method is tested on a decade's worth of housebreak data from Cambridge, MA.
The related papers, a Boston public radio interview and an article in the Boston Globe can be found here: http://projects.iq.harvard.edu/applied_stats/event/cynthia-rudin-mit
As per usual, our meeting will be held at 12 noon in CGIS K354<http://projects.iq.harvard.edu/applied_stats/2013-fall-0> and lunch will be served!
Tess
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Tess Wise
PhD Candidate
Harvard Department of Government
http://tesswise.com
