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Journal of the American Statistical Association Volume 106, 2011 - Issue 494
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Applications and Case Studies

Multivariate Regression Analysis for the Item Count Technique

Kosuke Imai Kosuke Imai is Assistant Professor, Department of Politics, Princeton University, Princeton NJ 08544. Additional statistical methods useful for item count technique are developed in the companion article (Blair and Imai 2010b). The open-source software, list: Statistical Methods for the Item Count Technique and List Experiment, is available for download at the Comprehensive R Archive Network (http://cran.r-project.org/package=list). Previous versions of this article were ciculated under the title of “Statistical Inference for the Item Count Technique.” I thank Thomas Yee for his help in fitting the Beta-Binomial model and useful comments. Thanks also to Graeme Blair, Patrick Brandt, and Adam Glynn for useful discussions. Detailed comments from the associate editor and anonymous referees significantly improved the presentation and analysis of this article. The Institute for Quantitative Social Science at Harvard University provided the computational support for the simulation studies. Financial support from the NSF grant (SES–0849715) is acknowledged.
Pages 407-416 | Received 01 Jun 2010, Published online: 24 Jan 2012

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