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Experimentation order in factorial designs: new findings

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  • Alexander A. Correa
  • Pere Grima
  • Xavier Tort-Martorell

Abstract

Under some very reasonable hypotheses, it becomes evident that randomizing the run order of a factorial experiment does not always neutralize the effect of undesirable factors. Yet, these factors do have an influence on the response, depending on the order in which the experiments are conducted. On the other hand, changing the factor levels is many times costly; therefore it is not reasonable to leave to chance the number of changes necessary. For this reason, run orders that offer the minimum number of factor level changes and at the same time minimize the possible influence of undesirable factors on the experimentation have been sought. Sequences which are known to produce the desired properties in designs with 8 and 16 experiments can be found in the literature. In this paper, we provide the best possible sequences for designs with 32 experiments, as well as sequences that offer excellent properties for designs with 64 and 128 experiments. The method used to find them is based on a mixture of algorithmic searches and an augmentation of smaller designs.

Suggested Citation

  • Alexander A. Correa & Pere Grima & Xavier Tort-Martorell, 2012. "Experimentation order in factorial designs: new findings," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(7), pages 1577-1591, January.
    • Handle: RePEc:taf:japsta:v:39:y:2012:i:7:p:1577-1591
    DOI: 10.1080/02664763.2012.661706
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    References listed on IDEAS

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    1. Guillermo De Leon Adams & Pere Grima Cintas & Xavier Tort-Martorell Llabres, 2005. "Experimentation order in factorial designs with 8 or 16 runs," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(3), pages 297-313.
    2. Alexander Correa & Pere Grima & Xavier Tort-Martorell, 2009. "Experimentation order with good properties for 2k factorial designs," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 743-754.
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