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19 September 2005

Conference on Methods in Health Services and Outcomes in Boston, October 28-30

Sebastian Bauhoff

Boston will host the 2005 International Conference on Health Policy Research from October 28-30. This year's theme is "Methodological Issues in Health Services and Outcomes Research" and presentations are meant to convey both content and methodology.

The conference includes a slightly eclectic selection of workshops on methods and the use of well-known health datasets -- two workshops on the latter are free, others cost $60 or $30 (students). Registration is not free either but studentes pay only $80. Looks interesting and useful overall, though you might want to attend selectively.

For more info check the conference website.

Posted by SSS Coauthors at 10:50 PM

Applied Stats Seminar

Michael Kellermann

The Research Workshop in Applied Statistics brings together the statistical community at Harvard for a lively exchange of ideas. It is a forum for graduate students, faculty, and visiting scholars to present and discuss their work. We advertise the workshop as "a tour of Harvard's statistical innovations and applications," with weekly stops in different disciplines such as economics, epidemiology, medicine, political science, psychology, public policy, public health, sociology and statistics. The topics of papers presented in recent years include matching estimators, missing data, Bayesian simulation, sample selection, detecting biological attacks, imaging the Earth's interior, incumbency in primary elections, the effects of marriage on crime, and revealed preference rankings of universities.

One of the strengths of the workshop is its diverse group of faculty sponsors. This year's sponsors include Alberto Abadie (Kennedy School), Garrett Fitzmaurice (School of Public Health), Lee Fleming (Business School), Guido Imbens (Economics), Gary King (Government), Kevin Quinn (Government), James Robins (School of Public Health), Donald Rubin (Statistics), and Christopher Winship (Sociology). The workshop provides an excellent opportunity for informal interaction between graduate students and faculty.

The workshop meets Wednesdays during the academic year; lunch is provided. If you are interested, come to our organizational meeting on Wednesday, September 21 at noon in Room N354 at the Institute for Quantitative Social Science (IQSS is located on the 3rd Floor of CGIS North, 1737 Cambridge St., located behind the Design School). Course credit is available for students as an upper-level class in either Government or Sociology.

For more information, check out our website at here . There you will find contact information, the schedule of presentations, and links to papers from previous presentations. We'll also be using this blog to announce speakers and to post reports from the workshop, so check back here often. We hope to see many of you there. If you have any questions, feel free to e-mail me at kellerm@fas.harvard.edu.

Posted by James Greiner at 12:53 PM

Censoring Due to Death, cont'd, & A Visit To Harvard

Censoring, cont'd
John F. Friedman

Continuing from the most recent post, for the economist, perhaps a more interesting incidence of this statistical problem is not researchers making this error within the literature but consumers making misjudgments in the marketplace. (Since most people approach problems in their lives with less rigor than a statistician, perhaps this is not surprising). In particular, once consumers make these inference mistakes, economic theory suggests that firms will take advantage. Edward Glaeser wrote at length on this phenomenon in 2003 in "Psychology and the Market."

One classic example of this phenomenon - as specifically related to censorship by death - is the mutual fund industry. Most brochures for management companies aggressively tout the high past returns that have accumulated in their funds. Consumers then extrapolate these historical earnings into the future, usually choosing managers based on past performance. Of course, their reasoning is tainted by the same statistical problem; companies will shut down those mutual funds which have poor past performance, leaving only their winners for customers to admire. (Another problem with this line of reasoning is that there is virtually no evidence that strong past performance predicts of strong future performance. In this sense, perhaps the greater error is to pay attention to past returns at all!) This problem is compounded in the market by the fact that any firm which attempts to educate consumers about their mistakes is unlikely to capture the value-added from that effort. The now-savvy consumers have no reason to invest at the firm that provided the information, and, even if they did, these firms make the most money from naive consumers rather the smart ones, who would now make up the clientele. See David Laibson and Xavier Gabaix (2004) for more on this phenomenon. Since no firm has an incentive to educate the public, the entire industry becomes geared towards taking advantage of naive consumers, obfuscating costs, and selectively presenting information.

A Visit To Harvard

Anton Westveld (Visiting from University of Washington Statistics Department)

This past week I had the opportunity to visit with Kevin Quinn, one of my main Ph.D. advisors, at for the Center for Government and International Studies at Harvard. Kevin and Gary King asked if I would provide a brief description of my recent visit.

I was fortunate enough to arrive in time to work in the new buildings for the Center. The new space has a modern design that is quite beautiful and utilitarian.

Currently we are working on developing statistical methodology for longitudinal social network data. Social network data consist of measured relations occurring from interactions within a set of actors. This type of data allows for the empirical investigation of the interconnectivity of the actors, which is a cornerstone of social science theory. The methodology focuses on data generated from the repeated interaction of pairs of actors, including temporal dyadic data resulting in an outcome for each actor at each time point (e.g. the level of exports from Canada to Japan in a given year). The methodology incorporates structure to account for correlation resulting from interactions as well as the repeated nature of the data. In particular, a random effects model is employed which accounts for five different types of network dependencies. These five dependencies are then correlated over time through the assumption that the random effects follow a weakly stationary process.

Kevin and I spent the last few days discussing appropriate methodology and writing C++ code. We also spent some time discussing the relationship between social network models and statistical game theory models, both of which seek to gain an understating of social phenomena by examining social interaction data. Due to the Center’s collegial environment, I also had opportunities to discuss my work with Gary King and Jake Bowers.

Posted by James Greiner at 7:00 AM