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Replication with Attention to Numerical Accuracy

Published online by Cambridge University Press:  04 January 2017

Micah Altman  and
Michael P. McDonald
Micah Altman
Affiliation:
Harvard-MIT Data Center Harvard University, Cambridge, MA 02138. e-mail: micah_altman@harvard.edu
Michael P. McDonald
Affiliation:
Department of Public and International Affairs, George Mason University, 4400 University Drive-3F4, Fairfax, VA 22030-4444. e-mail: mmcdona5@gmu.edu
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Abstract

Numerical issues matter in statistical analysis. Small errors occur when numbers are translated from paper and pencil into the binary world of computers. Surprisingly, these errors may be propagated and magnified through binary calculations, eventually producing statistical estimates far from the truth. In this replication and extension article, we look at one method of verifying the accuracy of statistical estimates by running these same data and models on multiple statistical packages. We find that for two published articles, Nagler (1994, American Journal of Political Science 38:230-255) and Alvarez and Brehm (1995, American Journal of Political Science 39:1055-1089), results are dependent on the statistical package used. In the course of our replications, we uncover other pitfalls that may prevent accurate replication, and make recommendations to ensure the ability for future researchers to replicate results.

Type
Replications and Extensions
Information
Political Analysis , Volume 11 , Issue 3 , Summer 2003 , pp. 302 - 307
Copyright
Copyright © Political Methodology Section of the American Political Science Association 2003 

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References

Altman, Micah, and McDonald, Michael P. 2001. “Choosing Reliable Statistical Software.” PS: Political Science and Politics 43:681–687.Google Scholar
Altman, Micah, Gill, Jeff, and McDonald, Michael P. 2003. Statistical Computing for the Social Sciences. Beverly Hills, CA: Wiley.Google Scholar
Alvarez, R. Michael, and Brehm, John. 1995. “American Ambivalence Towards Abortion Policy: Development of a Hetreoskedastic Probit Model of Competing Values.” American Journal of Political Science 39:1055–1089.CrossRefGoogle Scholar
Kaiser, Jocelyn. 2002. “Software Glitch Threw off Mortality Estimates.” Science 296:1945–1946.Google Scholar
Nagler, Jonathan. 1994. “Scobit: An Alternative Estimator to Logit and Probit.” American Journal of Political Science 38:230–255.Google Scholar
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