The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
A Statistical Model for Multiparty Electoral Data
Abstract
We propose a comprehensive statistical model for analyzing multiparty, district-level elections. This model, which provides a tool for comparative politics research analogous to that which regression analysis provides in the American two-party context, can be used to explain or predict how geographic distributions of electoral results depend upon economic conditions, neighborhood ethnic compositions, campaign spending, and other features of the election campaign or aggregate areas. We also provide new graphical representations for data exploration, model evaluation, and substantive interpretation. We illustrate the use of this model by attempting to resolve a controversy over the size of and trend in the electoral advantage of incumbency in Britain. Contrary to previous analyses, all based on measures now known to be biased, we demonstrate that the advantage is small but meaningful, varies substantially across the parties, and is not growing. Finally, we show how to estimate the party from which each party's advantage is predominantly drawn.
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Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Designing Social Inquiry: Scientific Inference in Qualitative Research
King, G., Keohane, R. O., & Verba, S. (1994) · Princeton University Press · doi:10.1515/9781400821211 · Cited by 7,225
Self-citationKuper, L., & Horowitz, D. L. (1986) · Contemporary Sociology · doi:10.2307/2069338 · Cited by 4,869
The Statistical Analysis of Compositional Data
Aitchison, J. (1986) · doi:10.1007/978-94-009-4109-0 · Cited by 4,383
Democracy and the Market: Political and Economic Reforms in Eastern Europe and Latin America
Przeworski, A. (1991) · doi:10.1017/cbo9781139172493 · Cited by 3,494
The Statistical Analysis of Compositional Data
Piepel, G. F. (1988) · Technometrics · doi:10.1080/00401706.1988.10488337 · Cited by 3,418
Making the most of statistical analyses: improving interpretation and presentation
King, G., Tomz, M., & Wittenberg, J. (2000) · American Journal of Political Science · doi:10.2307/2669316 · Cited by 3,232
Self-citationA Cross-National Analysis of Economic Voting: Taking Account of the Political Context
Powell, G. B., & Whitten, G. D. (1993) · American Journal of Political Science · doi:10.2307/2111378 · Cited by 2,158
Distributions in Statistics: Continuous Multivariate Distributions.
Gokhale, D. V., Johnson, N. L., & Kotz, S. (1973) · Biometrics · doi:10.2307/2529696 · Cited by 1,599
Economics and elections: the major western democracies
(1989) · Choice Reviews Online · doi:10.5860/choice.27-1158 · Cited by 1,340
Cited by
Making the most of statistical analyses: improving interpretation and presentation
King, G., Tomz, M., & Wittenberg, J. (2000) · American Journal of Political Science · doi:10.2307/2669316 · Cited by 3,232
Self-citationAmelia II: A Program for Missing Data
Honaker, J., King, G., & Blackwell, M. (2011) · Journal of Statistical Software · doi:10.18637/jss.v045.i07 · Cited by 2,552
Self-citationAnalyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation
King, G., Honaker, J., Joseph, A., & Scheve, K. (2001) · American Political Science Review · doi:10.1017/s0003055401000235 · Cited by 1,834
Self-citationScaling Down: The Subnational Comparative Method
Snyder, R. (2001) · Studies in Comparative International Development · doi:10.1007/bf02687586 · Cited by 1,002
Eggers, A. C., Fowler, A., Hainmueller, J., Hall, A. B., & Snyder, J. M. (2015) · American Journal of Political Science · doi:10.1111/ajps.12127 · Cited by 423
Metadata
- Authors
- Katz, J. N., & King, G.
- Venue
- American Political Science Review
- Publisher
- Cambridge University Press (CUP)
- Published
- 1999-03
- Volume
- 93
- Issue
- 1
- Pages
- 15-32
- ISSN
- 0003-0554 (ISSN-L)
- 1537-5943
- OpenAlex
- W3122632052
- Cited by
- 292
- References
- 40
- FWCI
- 36.97
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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