gov3009-l September 2008

gov3009-l@lists.fas.harvard.edu

1 participants
3 discussions

King on "Matching for Causal Inference Without Balance Checking"

by Justin Grimmer

Dear Applied Statistics Community, Please join us on Wednesday October 1st when Gary King, the David Florence Professor of Government, will present "Matching for Causal Inference Without Balance Checking". A draft of the paper is available here: http://gking.harvard.edu/files/cem.pdf , and here is the abstract: We address a major discrepancy in matching methods for causal inference in observational data. Since these data are typically plentiful, the goal of matching is to reduce bias and only secondarily to keep variance low. However, most matching methods seem designed for the opposite problem, guaranteeing sample size ex ante but limiting bias by controlling for covariates through reductions in the imbalance between treated and control groups only ex post and only sometimes. (The resulting practical difficulty may explain why many published applications do not check whether imbalance was reduced and so may not even be decreasing bias.) We introduce a new class of "Monotonic Imbalance Bounding" (MIB) matching methods that enables one to choose a fixed level of maximum imbalance, or to reduce maximum imbalance for one variable without changing it for the others. We then discuss a specific MIB method called "Coarsened Exact Matching" (CEM) which, unlike most existing approaches, also explicitly bounds through ex ante user choice both the degree of model dependence and the causal effect estimation error, eliminates the need for a separate procedure to restrict data to common support, meets the congruence principle, is approximately invariant to measurement error, works well with modern methods of imputation for missing data, is computationally efficient even with massive data sets, and is easy to understand and use. This method can improve causal inferences in a wide range of applications, and may be preferred for simplicity of use even when it is possible to design superior methods for particular problems. We also make available open source software which implements all our suggestions. The applied statistics workshop meets in room K-354, CGIS–Knafel (1737 Cambridge St) at 12 noon, with a light-lunch served. The presentation will begin at 1215 and the workshop usually ends around 130. All are welcome to attend, Cheers Justin Grimmer

15 years, 7 months

Benjamin Fry and Data Visualization

by Justin Grimmer

Dear Applied Statistics Community, Please join us tomorrow (Wednesday, 9/24) when we welcome Ben Fry to the applied statistics workshop. Ben's research explores data visualization—more details can be found here (http://benfry.com) -- including details of his recently completed book "Data Visualization" and samples from his previous work (http://benfry.com/projects/). The workshop will meet at 12 noon in room K-354, CGIS-Knafel (1737 Cambridge St) with a light lunch served. The presentation will begin at 1215 and usually ends around 130 pm. All are welcome— Cheers, Justin Grimmer

15 years, 7 months

Gelman on "Red State, Blue State, Rich State, Poor State"

by Justin Grimmer

Dear Applied Statistics Community, Welcome back for the 2008-2009 academic year. We have an exciting lineup of speakers this coming semester. The workshop kicks off this coming Wednesday, September 17th, with Andrew Gelman, Department of Statistics and Political Science, Columbia University. Andrew will be presenting results from his recently released book "Red State, Blue State, Rich State, Poor State". Here is an introduction to the book from the publisher: With wit and prodigious number crunching, Andrew Gelman and his coauthors get to the bottom of why Democrats win elections in wealthy states while Republicans get the votes of richer voters, how the two parties have become ideologically polarized, and other issues. Gelman uses eye-opening, easy-to-read graphics to unravel the mystifying patterns of recent voting, and in doing so paints a vivid portrait of the regional differences that drive American politics. He demonstrates in the plainest possible terms how the real culture war is being waged among affluent Democrats and Republicans, not between the haves and have-nots; how religion matters for higher-income voters; how the rich-poor divide is greater in red not blue states--and much more. With the excitement surrounding the current presidential races, this presentation promises to be informative to anyone interested in separating the facts from the myths about vote choice in America. For those interested, a blog is available about the book <http://redbluerichpoor.com/> , which is also available for purchase<http://www.amazon.com/gp/product/069113927X?ie=UTF8&tag=restblstristp-20&li…> . As a reminder, the applied statistics workshop meets every Wednesday in CGIS-Knafel, 1737 Cambridge St, room K-354 (Previously N-354, before the Chad Johnson/Prince-esque name change that recently swept through the north building). We start at 12 noon with a light lunch and the presentations usually begin around 1215. To give Andrew the maximum amount of time, we will skip the normal "business" meeting that usually starts the year. If anyone has any suggestions about how the workshop could improve, or would like to present at the workshop this year, please let me know (email would probably be the quickest and most effective method) Cheers Justin Grimmer

15 years, 7 months

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gov3009-l September 2008