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Replication with Attention to Numerical Accuracy

Author

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  • Altman, Micah
  • McDonald, Michael P.
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.

Suggested Citation

  • Altman, Micah & McDonald, Michael P., 2003. "Replication with Attention to Numerical Accuracy," Political Analysis, Cambridge University Press, vol. 11(3), pages 302-307, July.
    • Handle: RePEc:cup:polals:v:11:y:2003:i:03:p:302-307_01
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    Cited by:

    1. B. D. McCullough & H. D. Vinod, 2003. "Verifying the Solution from a Nonlinear Solver: A Case Study," American Economic Review, American Economic Association, vol. 93(3), pages 873-892, June.
    2. A. Yalta & A. Yalta, 2010. "Should Economists Use Open Source Software for Doing Research?," Computational Economics, Springer;Society for Computational Economics, vol. 35(4), pages 371-394, April.
    3. William D. Berry & Jacqueline H. R. DeMeritt & Justin Esarey, 2010. "Testing for Interaction in Binary Logit and Probit Models: Is a Product Term Essential?," American Journal of Political Science, John Wiley & Sons, vol. 54(1), pages 248-266, January.
    4. Altman, Micah & Gill, Jeff & McDonald, Michael P., 2007. "accuracy: Tools for Accurate and Reliable Statistical Computing," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i01).

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