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Orthogonal parallel-flats designs for hierarchical models

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  • Liao, C. T.

Abstract

Orthogonal designs are very popular in many experimental studies because of their optimality properties, ease of analysis, and ease of interpretation. In this paper, we prove a necessary and sufficient condition for a parallel-flats design to be orthogonal for estimating the factorial effects of hierarchical models for general s1n1xs2n2x...xsgng mixed factorial experiments, where s1,s2,...,sg are assumed to be distinct primes. Some examples are given to illustrate the results.

Suggested Citation

  • Liao, C. T., 2000. "Orthogonal parallel-flats designs for hierarchical models," Statistics & Probability Letters, Elsevier, vol. 46(4), pages 329-335, February.
    • Handle: RePEc:eee:stapro:v:46:y:2000:i:4:p:329-335
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    Cited by:

    1. Liao, C. T., 2001. "Some classes of orthogonal 2n1x3n2 mixed factorial designs of median-resolution," Statistics & Probability Letters, Elsevier, vol. 52(4), pages 401-411, May.

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