IDEAS home Printed from https://ideas.repec.org/a/bla/anzsta/v62y2020i4p407-425.html
   My bibliography  Save this article

Projection properties of three‐level screening designs

Author

Listed:
  • Mohammed A. Alomair
  • Stelios D. Georgiou
  • Manohar Aggarwal

Abstract

Screening designs are important for finding the factors that have a major effect on industrial experiments. In regard to quantitative factors, certain experimenters prefer three‐level rather than two‐level factors because having three levels can provide some assessments for capturing curvature in the response. In a recent paper, Jones and Nachtsheim, Journal of Quality Technology43, 1–15, proposed a new class of designs called definitive screening designs. Definitive screening designs have more favourable properties than classical screening designs. In this paper, we study the projection properties of three‐level screening designs. The comparison is based on several criteria such as D‐efficiency, G‐efficiency, A‐efficiency and average of variance over a range of models that include main effects, interaction and quadratic terms. New designs are generated as projections of the full designs into a smaller factor dimensional space. The best projections and their properties are presented in a tabular form.

Suggested Citation

  • Mohammed A. Alomair & Stelios D. Georgiou & Manohar Aggarwal, 2020. "Projection properties of three‐level screening designs," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 62(4), pages 407-425, December.
    • Handle: RePEc:bla:anzsta:v:62:y:2020:i:4:p:407-425
    DOI: 10.1111/anzs.12306
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/anzs.12306
    Download Restriction: no
    File URL: https://libkey.io/10.1111/anzs.12306?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
    ---><---

    References listed on IDEAS

    as
    1. Yong-Dao Zhou & Hongquan Xu, 2017. "Composite Designs Based on Orthogonal Arrays and Definitive Screening Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1675-1683, October.
    2. Lin, Dennis K. J. & Draper, Norman R., 1993. "Generating alias relationships for two-level Plackett and Burman designs," Computational Statistics & Data Analysis, Elsevier, vol. 15(2), pages 147-157, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. SCHOEN, Eric D. & VO-THANH, Nha & GOOS, Peter, 2015. "Two-level orthogonal designs in 24 and 28 runs," Working Papers 2015016, University of Antwerp, Faculty of Business and Economics.
    2. SCHOEN, Eric D. & MEE, Robert W., 2012. "Two-level designs of strength 3 and up to 48 runs," Working Papers 2012005, University of Antwerp, Faculty of Business and Economics.
    3. Kolaiti, E. & Koukouvinos, C., 2006. "On the use of three level orthogonal arrays in robust parameter design," Statistics & Probability Letters, Elsevier, vol. 76(3), pages 266-273, February.
    4. Lawson, John, 2002. "Regression analysis of experiments with complex confounding patterns guided by the alias matrix," Computational Statistics & Data Analysis, Elsevier, vol. 39(2), pages 227-241, April.
    5. Eric D. Schoen & Nha Vo-Thanh & Peter Goos, 2017. "Two-Level Orthogonal Screening Designs With 24, 28, 32, and 36 Runs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1354-1369, July.
    6. Emanuele Borgonovo & Elmar Plischke & Giovanni Rabitti, 2022. "Interactions and computer experiments," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1274-1303, September.
    7. Großmann, Heiko & Gilmour, Steven G., 2023. "Partially orthogonal blocked three-level response surface designs," Econometrics and Statistics, Elsevier, vol. 28(C), pages 138-154.

    More about this item

    Statistics

    Access and download statistics

    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:bla:anzsta:v:62:y:2020:i:4:p:407-425. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=1369-1473 .

    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.