The design of optimum multifactorial experiments.

PLACKETT, R. L., & BURMAN, J. P. (1946). The design of optimum multifactorial experiments. Biometrika, 33(4), 305-325.

Type

Journal article

Intellectual base

Primary research

Year

1946

DOI

10.1093/biomet/33.4.305

Link

https://doi.org/10.1093/biomet/33.4.305

Cited from

statistics_experimental_design

Cited by

3 citations across 3 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Blocking (In Experimental Design)
  • This pre-specification is a feature for transparency and analytic cleanliness but a bug when the experimenter realizes mid-experiment that a different blocking variable would have been more informative

    This sourceFoundational screening/fractional-factorial designs requiring ex-ante specification of the factors to be studied

• Factorial Design
  • 4. The fractional-factorial trade-off (resolution and aliasing) — fractional designs (2^(k-p) designs studying k factors in fewer than 2^k runs) trade the ability to estimate high-order interactions for dramatic run-count reduction, via aliasing assumptions: high-order interactions are assumed small or absent

    This sourceintroduces screening designs that study k factors in as few as k+1 runs by aliasing main effects with higher-order interactions, the fractional-factorial trade-off and aliasing-assumption (effect-sparsity) the markers cite.

• Randomization

  • This sourcePlackett Burman screening fractional-factorial randomization efficiency.

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