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On the usage of refined linear models for determiningN-way classification designs which are optimal for comparing test treatments with a standard treatment

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Summary

In this paper we consider experimental settings in whichv test treatments are to be compared to some control or standard treatment and where heterogeneity needs to be eliminated inn-directions. Using techniques similar to those used by Kunnert (1983,Ann. Statist.,11, 247–257) concerning the determination of optimal designs under a refined linear model, some methods are given for constructingn-way classification designs which areA- andMV-optimal for estimating elementary treatment differences involving the standard treatment fromm-way classification designs,m<n, which areA- andMV-optimal for estimating the same treatment differences. Examples are given for the casen=2 to show how the results obtained can be applied.

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Authors and Affiliations

  1. Washington State University, Washington, USA

    Mike Jacroux

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  1. Mike Jacroux
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Additional information

This research was supported by NSF grant No. DMS-8401943.

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Jacroux, M. On the usage of refined linear models for determiningN-way classification designs which are optimal for comparing test treatments with a standard treatment. Ann Inst Stat Math 38, 569–581 (1986). https://doi.org/10.1007/BF02482544

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  • DOI: https://doi.org/10.1007/BF02482544

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