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A generalization of the alias matrix

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  • Murat Kulahci
  • Søren Bisgaard

Abstract

The investigation of aliases or biases is important for the interpretation of the results from factorial experiments. For two-level fractional factorials this can be facilitated through their group structure. For more general arrays the alias matrix can be used. This tool is traditionally based on the assumption that the error structure is that associated with ordinary least squares. For situations where that is not the case, we provide in this article a generalization of the alias matrix applicable under the generalized least squares assumptions. We also show that for the special case of split plot error structure, the generalized alias matrix simplifies to the ordinary alias matrix.

Suggested Citation

  • Murat Kulahci & Søren Bisgaard, 2006. "A generalization of the alias matrix," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(4), pages 387-395.
    • Handle: RePEc:taf:japsta:v:33:y:2006:i:4:p:387-395
    DOI: 10.1080/02664760500449014
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    Cited by:

    1. Armando Javier Ríos-Lira & Yaquelin Verenice Pantoja-Pacheco & José Antonio Vázquez-López & José Alfredo Jiménez-García & Martha Laura Asato-España & Moisés Tapia-Esquivias, 2021. "Alias Structures and Sequential Experimentation for Mixed-Level Designs," Mathematics, MDPI, vol. 9(23), pages 1-21, November.

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