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Related Experiment Videos

Factorial designs for crossover clinical trials.

D J Fletcher1, S M Lewis, J N Matthews

  • 1Department of Biometry, School of Crop Sciences, University of Sydney, NSW, Australia.

Statistics in Medicine
|October 1, 1990
PubMed
Summary

This study introduces a flexible method for combining factorial and crossover designs to efficiently measure the joint effects of multiple factors. The approach uses

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Area of Science:

  • Experimental Design
  • Statistical Methodology
  • Industrial Experimentation

Background:

  • Measuring the joint effect of multiple factors typically employs factorial designs.
  • Crossover designs can enhance efficiency in suitable applications.
  • Combining factorial and crossover designs presents a challenge for experimental efficiency.

Purpose of the Study:

  • To present a flexible method for amalgamating factorial and crossover designs.
  • To enable the construction of experimental designs tailored to specific objectives.
  • To improve the efficiency of measuring joint effects of factors.

Main Methods:

  • Designs are constructed from smaller components called 'bricks'.
  • Bricks are generated cyclically from initial sequences.
  • Efficiencies of bricks for estimating direct treatment main effects and interactions are known and combined.

Main Results:

  • The method allows for the approximation of overall design efficiencies by combining brick efficiencies.
  • This facilitates the creation of customized experimental designs.
  • The approach is demonstrated for three and four periods with two factors having up to four levels.

Conclusions:

  • The proposed method offers a flexible and efficient way to combine factorial and crossover designs.
  • It provides a systematic approach for constructing tailored experimental designs.
  • This facilitates more efficient measurement of joint factor effects in various applications.

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