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    David Jensen "Using Graphical Models to Reason About Quasi-Experimental Designs"


    Effective methods for inferring causal dependence from observational data have been developed within both computer science and quantitative social science. Methods in computer science have focused on the correspondence between casual graphical models and observed patterns of statistical association. Methods in social science have focused on templates for causal inference often called quasi-experimental designs, including designs that use instrumental variables, propensity scores matching, regression discontinuity, and interrupted time-series. In this talk, I will describe many of the known experimental and quasi-experimental designs in the language of directed graphical models, and I will show how the graphical model framework allows effective reasoning about threats to validity in these designs. Finally, I will present two novel designs that have resulted from our recent work on causal inference in relational data.


    Bio: David Jensen is Associate Professor of Computer Science and Director of the Knowledge Discovery Laboratory at the University of Massachusetts Amherst. He received his doctorate from Washington University in St. Louis in 1992. From 1991 to 1995, he served as an analyst with the Office of Technology Assessment, an agency of the United States Congress. His research focuses on machine learning and causal inference in relational data sets, with applications to social network analysis, computational social science, fraud detection, and management of large technical systems. He has served on the Executive Committee of the ACM Special Interest Group on Knowledge Discovery and Data Mining and on the program committees of the International Conference on Machine Learning, the International Conference on Knowledge Discovery and Data Mining, and the Uncertainty in AI Conference. He was a member of the 2006-2007 Defense Science Study Group, and served for six years on DARPA's Information Science and Technology (ISAT) Group. He is the incoming Associate Director of the UMass Computational Social Science Initiative. He won the 2011 Outstanding Teaching Award from the UMass College of Natural Science.

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    /groups/cssi/search/index.rss?tag=hotlist/groups/cssi/search/?tag=hotWhat’s HotHotListHot!?tag=hot1/groups/cssi/sidebar/HotListterrieTerrie Kellogg2014-09-25 15:46:50+00:002014-09-25 15:46:50updated5terrieTerrie Kellogg2014-09-25 15:44:37+00:002014-09-25 15:44:37updated4Added tag - hotcscfCSCF2014-09-25 15:44:35+00:002014-09-25 15:44:35addTag3cscfCSCF2014-09-25 14:56:43+00:002014-09-25 14:56:43updated2First createdcscfCSCF2014-09-25 14:55:46+00:002014-09-25 14:55:46created1wiki2014-09-25T15:46:50+00:00groups/cssi/wiki/5f1a4False2013 Archives/groups/cssi/wiki/5f1a4/2013_Archives.htmlTerrie Kellogg5 updates2013 Archives This is a collection of videos of the Cross-Departmental Seminar Series events. February 1, 2013 - Brian F. Schaffner "Inequality and Repr...Falseterrie2014-09-25T15:46:50+00:00hot/groups/cssi/search/index.rss?sort=modifiedDate&kind=all&sortDirection=reverse&excludePages=wiki/welcomelist/groups/cssi/search/?sort=modifiedDate&kind=all&sortDirection=reverse&excludePages=wiki/welcomeRecent ChangesRecentChangesListUpdates?sort=modifiedDate&kind=all&sortDirection=reverse&excludePages=wiki/welcome0/groups/cssi/sidebar/RecentChangesListmodifiedDateallRecent ChangesRecentChangesListUpdateswiki/welcomeNo recent changes.reverse5search