Interdisciplinary Seminar in Quantitative Methods Archive 2013
About the workshops
The goal of the Interdisciplinary Seminar in Quantitative Methods is to provide an interdisciplinary environment where researchers can present and discuss cutting-edge research in quantitative methodology. The talks are aimed at a broad audience, with emphasis on conceptual rather than technical issues. The research presented is varied, ranging from new methodological developments to applied empirical papers that use methodology in an innovative way. We welcome speakers and audiences from all disciplines and fields, including the social, natural, biomedical, and behavioral sciences.
2013-2014 Series
Machine Learning Methods for Individualizing Just in Time Adaptive Interventions
September 11, 2013: Susan Murphy, Statistics, University of Michigan
The Analysis of Survey Data: Past Controversies, Current Orthodoxy, and a Proposed Future Paradigm
September 25, 2013: Rod Little, Biostatistics, University of Michigan
Using Vote Counts’ Digits to Diagnose Elections (Strategies, Vote Buying and Frauds)
October 9, 2013: Walter Mebane, Political Science/Statistics, University of Michigan
Double Sampling for Missing Outcome Data in Randomized Experiments
October 23, 2013: Donald Green, Political Science, Columbia University
Inverse Regression Analysis of Text Data
November 6, 2013: Matt Taddy, Statistics, Chicago Booth, University of Chicago
Design-Based Analysis of Regression Discontinuities: Some Advantages and Difficulties
November 20, 2013: Thad Dunning, Political Science, University of California at Berkeley
Public Policy in an Uncertain World
December 4, 2013: Chuck Manski, Economics, Northwestern University
The Balance-Sample Size Frontier in Matching Methods for Causal Inference
January 24, 2014: Gary King, Political Science, Harvard University
Are Participants Good Evaluators?
March 12, 2014: Jeff Smith, Economics/Public Policy, University of Michigan
Control Function Approaches to Estimating Causal Effects
March 26, 2014: Jeff Wooldridge, Economics, Michigan State University
An Extreme-Scale Computational Approach to Redistricting Optimization
April 9, 2014: Wendy K Tam Cho, Political Science and National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign
Random Coefficient Models for Multi-site Randomized Trials With Inverse Probability of Treatment Weighting
April 23, 2014: Stephen W. Raudenbush, Sociology, University of Chicago
Inference on Causal Effects in a Generalized Regression Kink Design
May 7, 2014: Zhuan Pei, Economics, Brandeis University
Endogenous Stratification in Randomized Experiments
May 21, 2014: Alberto Abadie, Public Policy, HKS, Harvard University