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Three-Way and Higher-Order Nested Classifications

  • Hardeo Sahai
  • Mario Miguel Ojeda

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.

Keywords

Variance Component Random Effect Model Computing Software Negative Estimate Exact Confidence Interval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Hardeo Sahai
    • 1
  • Mario Miguel Ojeda
    • 2
  1. 1.Center for Addiction Studies School of MedicineUniversidad Central del CaribeBayamon, Puerto RicoUSA
  2. 2.Económico AdministrativaUniversidad VeracruzanaKalapa, VeracruzMéxico

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