Gill, Jeff and Hangartner, Dominik (2010) Circular data in political science and how to handle it. Political Analysis, 18 (3). pp. 316-336. ISSN 1047-1987
Full text not available from this repository.Abstract
There has been no attention to circular (purely cyclical) data in political science research. We show that such data exist and are mishandled by models that do not take into account the inherently recycling nature of some phenomenon. Clock and calendar effects are the obvious cases, but directional data are observed as well. We describe a standard maximum likelihood regression modeling framework based on the von Mises distribution, then develop a general Bayesian regression procedure for the first time, providing an easy-to-use Metropolis-Hastings sampler for this approach. Applications include a chronographic analysis of U.S. domestic terrorism and directional party preferences in a two-dimensional ideological space for German Bundestag elections. The results demonstrate the importance of circular models to handle periodic and directional data in political science.
| Item Type: | Article |
|---|---|
| Official URL: | http://pan.oxfordjournals.org/ |
| Additional Information: | © 2010 The Authors |
| Divisions: | Methodology |
| Subjects: | J Political Science > JA Political science (General) |
| Date Deposited: | 03 Oct 2012 13:10 |
| Last Modified: | 20 Nov 2024 03:51 |
| URI: | http://eprints.lse.ac.uk/id/eprint/46514 |
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