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Simulation Experiments and Significance Tests

In: Artificial Economics and Self Organization

Author

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  • Klaus G. Troitzsch

    (Universität Koblenz-Landau)

Abstract

The paper uses two formal models of simple processes in artificial worlds—one with and one without an analytical solution—to discuss the role of statistical analysis and significance tests of results from multiple simulation runs. Moreover the paper argues that it is not the sheer existence of an effect of input parameters on simulation results but the effect size which is the interesting outcome of a simulation and that significance tests of differences in means are much less important than the distribution of output variables which are more often than not non-normal distributions.

Suggested Citation

  • Klaus G. Troitzsch, 2014. "Simulation Experiments and Significance Tests," Lecture Notes in Economics and Mathematical Systems, in: Stephan Leitner & Friederike Wall (ed.), Artificial Economics and Self Organization, edition 127, pages 17-28, Springer.
    • Handle: RePEc:spr:lnechp:978-3-319-00912-4_2
    DOI: 10.1007/978-3-319-00912-4_2
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    Cited by:

    1. Lee, Ju-Sung & Filatova, Tatiana & Ligmann-Zielinska, Arika & Hassani-Mahmooei, Behrooz & Stonedahl, Forrest & Lorscheid, Iris & Voinov, Alexey & Polhill, J. Gareth & Sun, Zhanli & Parker, Dawn C., 2015. "The complexities of agent-based modeling output analysis," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 18(4).

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