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Design and Modeling Strategies for Mixture-of-Mixtures Experiments

Authors: Lulu Kang; V. Roshan Joseph; William A. Brenneman;

Design and Modeling Strategies for Mixture-of-Mixtures Experiments

Abstract

In mixture-of-mixtures experiments major components are defined as the components which themselves are mixtures of some other components, called minor components. Sometimes components are divided into different categories where each category is called a major component and the components within a major component become minor components. The special structure of the mixture-of-mixtures experiment makes the design and modeling approaches different from a typical mixture experiment. In this article we propose a new model called the major–minor model to overcome some of the limitations of the commonly used multiple-Scheffe model. We also provide a strategy for designing experiments that are much smaller in size than those based on the existing methods. We then apply the proposed design and modeling approach to a mixture-of-mixtures experiment conducted to formulate a new potato crisp. This article has supplementary material online.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Average
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