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Spatial Processes and Political Methodology: Introduction to the Special Issue

Published online by Cambridge University Press:  04 January 2017

Michael D. Ward  and
John O'Loughlin
Michael D. Ward
Affiliation:
Department of Political Science and Center for Statistics in the Social Sciences, University of Washington, Seattle, WA 98195, and Éspace Éurope, Université Pierre Mendès France, Grenoble, France, BP 38040. e-mail: [email protected]
John O'Loughlin
Affiliation:
Department of Geography & Institute of Behavioral Science, University of Colorado, Boulder, CO 80309. e-mail: [email protected]
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Extract

Recently in this journal, Gary Cox introduced a special issue by noting that “The spatial model is the workhorse theory of modern legislative studies” (Cox 2001, p. 189). In this special issue, the focus is on a different type of spatial model than that typically used in legislative studies. Specifically, we concentrate on models in which the data are dependent on one another as a result of geographic influences, broadly defined.

Type
Research Article
Information
Political Analysis , Volume 10 , Issue 3: Special Issue on Spatial Methods in Political Science , Summer 2002 , pp. 211 - 216
Copyright
Copyright © Political Methodology Section of the American Political Science Association 2002 

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References

Agnew, John A. 1987. Place and Politics: The Geographical Mediation of State and Society. Boston: Allen and Unwin.Google Scholar
Agnew, John A. 1989. “The Devaluation of Space in Social Science.” In The Power of Place: Bringing Together the Geographical and Sociological Imaginations, eds. Agnew, John A. and Duncan, James S. Boston: Unwin Human, pp. 9–29.Google Scholar
Anselin, Luc. 1995. “Local Indicators of Spatial Association—LISA.” Geographical Analysis 27:93–115.Google Scholar
Berry, Brian J.L., and Marble, Duane F., eds. 1968. Spatial Analysis: A Reader in Statistical Geography. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Besag, Julian E. 1972. “Nearest-Neighbour Systems and the Auto-Logistic Model for Binary Data.” Journal of the Royal Statistical Society, Series B, Methodological 34:75–83.Google Scholar
Besag, Julian E. 1974. “Spatial Interaction and the Statistical Analysis of Lattice Systems (with Discussion).” Journal of the Royal Statistical Society, Series B, Methodological 36:192–225.Google Scholar
Besag, Julian E. 1977. “Errors-in-Variables Estimation for Gaussian Lattice Schemes.” Journal of the Royal Statistical Society, Series B, Methodological 39:73–74.Google Scholar
Besag, Julian E. 1981. “On a System of Two-Dimensional Recurrence Equations.” Journal of the Royal Statistical Society, Series B, Methodological 43:302–309.Google Scholar
Besag, Julian E., Milne, Robin, and Zachary, Stan. 1982. “Point Process Limits of Lattice Processes.” Journal of Applied Probability 19:210–216.Google Scholar
Besag, Julian E., and Moran, Patrick A. P. 1975. “On the Estimation and Testing of Spatial Interaction in Gaussian Lattice Processes.” Biometrika 62:555–562.Google Scholar
Besag, Julian, York, Jeremy, and Mollié, Annie. 1991. “Bayesian Image Restoration, with two Applications in Spatial Statistics (Disc: P21-59).” Annals of the Institute of Statistical Mathematics 43:1–59.Google Scholar
Chilès, Jean-Paul, and Delfiner, Pierre. 1999. Geostatistics: Modeling Spatial Uncertainty. New York: John Wiley.CrossRefGoogle Scholar
Cliff, Andrew D., and Keith Ord, J. 1981. Spatial Processes: Models and Applications. London: Pion.Google Scholar
Cox, Gary. 2001. “Introduction to the Special Issue.” Political Analysis 9:189–191.Google Scholar
Cressie, Noel A.C. 1991. Statistics for Spatial Data. New York: Wiley-Interscience.Google Scholar
Diggle, Peter J., Besag, Julian E., and Timothy Gleaves, J. 1976. ‘Statistical Analysis of Spatial Point Patterns by Means of Distance Methods.” Biometrics 32:659–667.Google Scholar
Diggle, Peter J., Moyeed, Rana A., and Tawn, Jonathan A. 1999. “Model Based Geostatistics, with Discussion.” Applied Statistics 47:299–350.Google Scholar
Fotheringham, A. Stewart. 1997. “Trends in Quantitative Methods, I: Stressing the Local.” Progress in Human Geography 21:88–96.Google Scholar
Fotheringham, A. Stewart, Brunsdon, Chris, and Charlton, Martin. 2000. Quantitative Geography: Perspectives on Spatial Data Analysis. Thousand Oaks, CA: Sage.Google Scholar
Gelman, Andrew, Carlin, John B., Stern, Hal S., and Rubin, David B. 1995. Bayesian Data Analysis. London: Chapman & Hall.Google Scholar
Griffith, Daniel A., and Layne, Larry J. 1999. A Casebook for Spatial Statistical Data Analysis: A Compilation of Analyses of Different Thematic Data Sets. New York: Oxford University Press.Google Scholar
Jackman, Simon. 2000. “Estimation and Inference Via Bayesian Simulation: An Introduction to Markov Chain Monte Carlo.” American Journal of Political Science 44:369–398.Google Scholar
Johnston, Ronald J. 1991. A Question of Place: Exploring the Practice of Human Geography. Oxford: Blackwell.Google Scholar
Longley, Paul D., and Batty, Michael. 1995. “Analysis, Modeling, Forecasting and GIS Technology.” In Geoinformational International, ed. Longley, Paul and Clarke, Graham. Cambridge: Cambridge University Press, pp. 1–16.Google Scholar
Moran, Patrick A.P. 1950. “A Test for Serial Independence of Residuals.” Biometrika 37:178–181.Google Scholar
Ord, J. Keith, and Getis, Arthur. 1995. “Local Spatial Autocorrelation Statistics: Distributional Issues and an Application.” Geographical Analysis 27:286–306.Google Scholar
Pred, Allan R. 1986. Place, Practice and Structure: Social and Spatial Transformation in Southern Sweden, 1750-1850. Totowa, NJ: Barnes and Noble.Google Scholar
Ripley, Brian D. 1988. Statistical Inference for Spatial Processes. Cambridge: Cambridge University Press.Google Scholar
Sheppard, Eric S. 2001. “Quantitative Geography: Representations, Practices, and Possibilities.” Environment and Planning D: Society and Space 19:535–554.Google Scholar