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Cross-Contamination in EI-R: Reply

Published online by Cambridge University Press:  04 January 2017

Michael C. Herron  and
Kenneth W. Shotts
Michael C. Herron
Affiliation:
Department of Political Science, Northwestern University, 601 University Place, Evanston, IL 60208-1006. e-mail: m-herron@northwestern.edu
Kenneth W. Shotts
Affiliation:
Department of Political Science, Northwestern University, 601 University Place, Evanston, IL 60208-1006. e-mail: k-shotts@northwestern.edu
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Extract

We address in Herron and Shotts (2003; hereinafter HS) an increasingly common statistical practice called EI-R, in which point estimates generated by the King (1997) ecological inference technique are used as dependent variables in second-stage linear regressions. Although HS argue that EI-R slope estimates are inconsistent and suffer from attenuation bias, this characterization of EI-R is excessively conservative. Indeed, we show here that EI-R estimates can suffer from sign reversals, attenuation bias, and augmentation bias, that inference based on these estimates can be misleading, and that EI-R is unfixable and should not be used.

Information

Type
Using EI in Second-Stage Regressions
Information
Political Analysis , Volume 11 , Issue 1 , Winter 2003 , pp. 77 - 85
Copyright
Copyright © Political Methodology Section of the American Political Science Association 2003 

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References

Adolph, Christopher, and King, Gary. 2003. “Analyzing Second-Stage Ecological Regressions: Comment on Herron and Shotts.” Political Analysis 11:65–76.CrossRefGoogle Scholar
Burden, Barry C., and Kimball, David C. 1998. “A New Approach to the Study of Ticket Splitting.” American Political Science Review 92:533–544.CrossRefGoogle Scholar
Burden, Barry C., and Kimball, David C. 2002. Why Americans Split Their Tickets: Campaigns, Competition, and Divided Government. Ann Arbor: The University of Michigan Press.CrossRefGoogle Scholar
Gay, Claudine. 2001. “The Effect of Black Congressional Representation on Political Participation.” American Political Science Review 95:589–602.CrossRefGoogle Scholar
Herron, Michael C., and Shotts, Kenneth W. 2000a. “A Specification Test for Linear Regressions That Use King-Based Ecological Inference Point Estimates as Dependent Variables.” Paper presented at the Annual Meeting of the American Political Science Association, Washington, DC.Google Scholar
Herron, Michael C., and Shotts, Kenneth W. 2000b. “Using Ecological Inference Point Estimates in Second Stage Linear Regressions.” Paper presented at the Society for Political Methodology Summer Conference, Los Angeles.Google Scholar
Herron, Michael C., and Shotts, Kenneth W. 2002. “Logical Inconsistency in King-Based Ecological Regressions.” Paper presented at the Society for Political Methodology Summer Conference, Seattle, WA.Google Scholar
Herron, Michael C., and Shotts, Kenneth W. 2003. “Using Ecological Inference Point Estimates as Dependent Variables in Second-Stage Linear Regressions.” Political Analysis 11:44–64.CrossRefGoogle Scholar
King, Gary. 1997. A Solution to the Ecological Inference Problem. Princeton, NJ: Princeton University Press.Google Scholar
McCue, Kenneth F. 2001. “The Statistical Foundations of the EI Method.” The American Statistician 55(2): 106–110.CrossRefGoogle Scholar