Author Information

Weiming Ke
Cuirong Ren
Huitian Lu

Abstract

Blocked two-level fractional factorial designs are a very useful tool for efficient data collection in agricultural and other scientific research. In most experiments, in addition to the main effects, some two-factor interactions are also meaningful and need to be estimated. We propose a method for efficiently selecting blocked two-level fractional factorial designs when some of the two-factor interactions are non-negligible. We then present some results for a design with only 8 or 16 runs to illustrate how to use this method.

Keywords

blocking factor; defining contrast subgroup; defining words; minimum aberration; resolution; word-length pattern; confounding pattern

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Apr 27th, 10:00 AM

SELECTION OF BLOCKED TWO-LEVEL FRACTIONAL FACTORIAL DESIGNS FOR AGRICULTURAL EXPERIMENTS

Blocked two-level fractional factorial designs are a very useful tool for efficient data collection in agricultural and other scientific research. In most experiments, in addition to the main effects, some two-factor interactions are also meaningful and need to be estimated. We propose a method for efficiently selecting blocked two-level fractional factorial designs when some of the two-factor interactions are non-negligible. We then present some results for a design with only 8 or 16 runs to illustrate how to use this method.