We present a technique for analyzing a simulation metamodel that has been constructed using a variance-stabilizing transformation. To compute a valid confidence interval for the expected value of the original simulation response at a selected factor-level combination (design point), we first compute the corresponding confidence interval for the transformed response at that factor-level combination and then untransform the endpoints of the resulting confidence interval. Taking the midpoint of the untransformed confidence interval as our point estimator of the expected simulation response at the selected factor-level combination and approximating the variance of this point estimator via the delta method, we formulate an approximate two-sample Student t-test for validating our metamodel-based estimator versus the results of making independent runs of the simulation at the selected factor-level combination. We illustrate this technique in a case study involving the design of a manufacturing cell, and we compare our results with those of a more conventional approach to analyzing transformed-based simulation metamodels. A Monte Carlo performance evaluation shows that significantly better confidence-interval coverage is maintained with the proposed procedure over a wide range of values for the residual variance of the transformed metamodel.

Date of creation, presentation, or exhibit



In the Proceedings of the 2000 Winter Simulation Conference, Piscataway, New Jersey, pp. 773--781, December 2000 Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type

Conference Proceeding

Department, Program, or Center

Industrial and Systems Engineering (KGCOE)


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