IDEAS home Printed from https://ideas.repec.org/a/spr/metrik/v76y2013i5p723-732.html
   My bibliography  Save this article

On simplifying the calculations leading to designs with general minimum lower-order confounding

Author

Listed:
  • Jia-Lin Wei
  • Jian-Feng Yang

Abstract

Motivated by the effect hierarchy principle, Zhang et al. (Stat Sinica 18:1689–1705, 2008 ) introduced an aliased effect number pattern (AENP) for regular fractional factorial designs and based on the new pattern proposed a general minimum lower-order confounding (GMC) criterion for choosing optimal $$2^{n-m}$$ designs. Zhang et al. (Stat Sinica 18:1689–1705, 2008 ) proved that most existing criteria can be obtained by functions of the AENP. In this paper we propose a simple method for the calculation of AENP. The method is much easier than before since the calculation only makes use of the design matrix. All 128-run GMC designs with the number of factors ranging from 8 to 32 are provided for practical use. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Jia-Lin Wei & Jian-Feng Yang, 2013. "On simplifying the calculations leading to designs with general minimum lower-order confounding," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(5), pages 723-732, July.
    • Handle: RePEc:spr:metrik:v:76:y:2013:i:5:p:723-732
    DOI: 10.1007/s00184-013-0442-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00184-013-0442-z
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00184-013-0442-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:metrik:v:76:y:2013:i:5:p:723-732. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.