Optimal Design

Fedorov, Valerii V.

doi:10.1002/9780470057339.vao008

Cited by 1 publication

(1 citation statement)

References 34 publications

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“…Most of the applications of optimal design to the chemical and biological sciences have been in the context of nonlinear regression models (environmental toxicology , systems biology , microbiology , and environmental engineering ), although chemometrics applications use it in the context of linear regression. More on optimal design can be found in the aforementioned books by Goos and Jones and Atkinson et al ; see also a description in an environmentrics context by Fedorov .…”

Section: Introductionmentioning

confidence: 99%

Selecting the best design for nonstandard toxicology experiments

Webb

Smucker

Bailer

2014

Enviro Toxic and Chemistry

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Although many experiments in environmental toxicology use standard statistical experimental designs, there are situations that arise where no such standard design is natural or applicable because of logistical constraints. For example, the layout of a laboratory may suggest that each shelf serve as a block, with the number of experimental units per shelf either greater than or less than the number of treatments in a way that precludes the use of a typical block design. In such cases, an effective and powerful alternative is to employ optimal experimental design principles, a strategy that produces designs with precise statistical estimates. Here, a D-optimal design was generated for an experiment in environmental toxicology that has 2 factors, 16 treatments, and constraints similar to those described above. After initial consideration of a randomized complete block design and an intuitive cyclic design, it was decided to compare a D-optimal design and a slightly more complicated version of the cyclic design. Simulations were conducted generating random responses under a variety of scenarios that reflect conditions motivated by a similar toxicology study, and the designs were evaluated via D-efficiency as well as by a power analysis. The cyclic design performed well compared to the D-optimal design.

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