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Stochastic Variation: A Comment on Lewis-Beck and Skalaban's “The R-Squared”

  • Gary King


In an interesting and provocative article, Michael Lewis-Beck and Andrew Skalaban make an important contribution by emphasizing several philosophical issues in political methodology that have received too little attention from methodologists and quantitative researchers. These issues involve the role of systematic, and especially stochastic, variation in statistical models. After briefly discussing a few points of disagreement, hoping to reduce them to points of clarification, I turn to the philosophical issues. Examples with real data follow.



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Edwards, A. W. F. 1972. Likelihood. Cambridge: Cambridge University Press.
Gelman, Andrew, and King, Gary. 1990. “Estimating Incumbency Advantage Without Bias.” American Journal of Political Science 34. Forthcoming.
King, Gary. 1986. “How Not to Lie with Statistics: Avoiding Common Mistakes in Quantitative Political Science.” American Journal of Political Science 30: 666–87.
9. Measured in variances, the stochastic variance left over from this regression is 22 percent of the observed total variance.
King, Gary. 1989. Unifying Political Methodology: The Likelihood Theory of Statistical Inference. New York: Cambridge University Press.
King, Gary, and Gelman, Andrew. 1991. “Systemic Consequences of Incumbency Advantage in the U.S. House.” American Journal of Political Science. Forthcoming.
Lewis-Beck, Michael S. 1980. Applied Regression: An Introduction. Beverly Hills: Sage.
Stigler, Stephen. 1986. The History of Statistics. Cambridge, Mass.: Harvard University Press.
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Political Analysis
  • ISSN: 1047-1987
  • EISSN: 1476-4989
  • URL: /core/journals/political-analysis
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