Advertisement

Split Plot Models

Chapter
  • 1.2k Downloads
Part of the Springer Texts in Statistics book series (STS)

Abstract

This chapter introduces a cluster sampling model and then adapts that model to develop generalizations of split plot models. Split plot models are among the simplest of the mixed models considered in ALM-III in that they involve only two independent error terms (or, equivalently, two variance components). The chapter closes with a discussion of issues related to properly identifying the existence of two random error terms

References

  1. Christensen, R. (2015). Analysis of variance, design, and regression: Linear modeling for unbalanced data (2nd ed.). Boca Raton, FL: Chapman and Hall/CRC Pres.Google Scholar
  2. Christensen, R. (1984). A note on ordinary least squares methods for two-stage sampling. Journal of the American Statistical Association, 79, 720–721.CrossRefGoogle Scholar
  3. Christensen, R. (1987). The analysis of two-stage sampling data by ordinary least squares. Journal of the American Statistical Association, 82, 492–498.MathSciNetCrossRefGoogle Scholar
  4. Cornell, J. A. (1988). Analyzing mixture experiments containing process variables. A split plot approach. Journal of Quality Technology, 20, 2–23.CrossRefGoogle Scholar
  5. Fisher, R. A. (1935). The design of experiments, (9th ed., 1971). New York: Hafner Press.Google Scholar
  6. Mathew, T., & Sinha, B. K. (1992). Exact and optimum tests in unbalanced split-plot designs under mixed and random models. Journal of the American Statistical Association, 87, 192–200.MathSciNetCrossRefGoogle Scholar
  7. Monlezun, C. J., & Blouin, D. C. (1988). A general nested split-plot analysis of covariance. Journal of the American Statistical Association, 83, 818–823.MathSciNetCrossRefGoogle Scholar
  8. Skinner, C. J., Holt, D., & Smith, T. M. F. (1989). Analysis of complex surveys. New York: Wiley.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Mathematics and StatisticsUniversity of New MexicoAlbuquerqueUSA

Personalised recommendations