Optimal two-level regular fractional factorial block and split-plot designs

Ching Shui Cheng, Pi-Wen Tsai

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

We propose a general and unified approach to the selection of regular fractional factorial designs, which can be applied to experiments that are unblocked, blocked or have a split-plot structure. Our criterion is derived as a good surrogate for the model-robustness criterion of information capacity. In the case of random block effects, it takes the ratio of intra- and interblock variances into account. In most of the cases we have examined, there exist designs that are optimal for all values of that ratio. Examples of optimal designs that depend on the ratio are provided. We also demonstrate that our criterion can further discriminate designs that cannot be distinguished by the existing minimum-aberration criteria.

Original languageEnglish
Pages (from-to)83-93
Number of pages11
JournalBiometrika
Volume96
Issue number1
DOIs
Publication statusPublished - 2009 Mar 1

Fingerprint

Split-plot Design
Fractional Factorial
Channel capacity
Split-plot
Minimum Aberration
Model Robustness
Information Capacity
Aberrations
Fractional Factorial Design
Experiments
Demonstrate
Experiment
Design

Keywords

  • Alias set
  • Estimation capacity
  • Information capacity
  • Minimum aberration
  • Model robustness
  • Word length pattern

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Statistics and Probability
  • Mathematics(all)
  • Applied Mathematics
  • Statistics, Probability and Uncertainty

Cite this

Optimal two-level regular fractional factorial block and split-plot designs. / Cheng, Ching Shui; Tsai, Pi-Wen.

In: Biometrika, Vol. 96, No. 1, 01.03.2009, p. 83-93.

Research output: Contribution to journalArticle

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