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Three-Way and Higher-Order Crossed Classifications

  • Hardeo Sahai
  • Mario Miguel Ojeda

Abstract

In the preceding two chapters, we considered random models involving two factors. In many fields of research, an investigator often works with experiments or surveys involving more than two factors; which entails simultaneous data collection under conditions determined by several factors. This type of design is usually more economical and can provide more information than separate one-way or two-way layouts. The analysis of variance of the two-way crossed model can be readily extended to situations involving three or more factors. In this chapter, we study random effects models involving three factors in somewhat greater detail. The extension of the model to experiments involving four or more factors is also indicated briefly.

Keywords

Variance Component Exact Confidence Interval Approximate Confidence Interval Closed Form Analytic Expression Uncorrelated Random Variable 
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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