IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-0-8176-8168-5_7.html
   My bibliography  Save this book chapter

Three-Way and Higher-Order Nested Classifications

In: Analysis of Variance for Random Models

Author

Listed:
  • Hardeo Sahai

    (Universidad Central del Caribe, Center for Addiction Studies School of Medicine)

  • Mario Miguel Ojeda

    (Universidad Veracruzana, Económico Administrativa)

Abstract

In the preceding chapter, we considered a random effects model involving a two-way nested classification. Examples of three and higher-order nested classifications occur frequently in many industrial experiments where raw material is first broken up into batches and then into subbatches, subsubbatches, and so forth. For example, in an experiment designed to identify various sources of variability in tensile strength measurements, one may randomly select a lots of raw material, b boxes are taken from each lot, c sample preparations are made from the material in each box, and finally n tensile strength tests are performed for each preparation. These factors often present themselves in a hierarchical manner and are appropriately specified as random effects. In this chapter, we consider a random effects model involving a three-way nested classification and indicate its generalization to higher-order nested classifications.

Suggested Citation

  • Hardeo Sahai & Mario Miguel Ojeda, 2004. "Three-Way and Higher-Order Nested Classifications," Springer Books, in: Analysis of Variance for Random Models, chapter 7, pages 333-381, Springer.
    • Handle: RePEc:spr:sprchp:978-0-8176-8168-5_7
    DOI: 10.1007/978-0-8176-8168-5_7
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:sprchp:978-0-8176-8168-5_7. 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.