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Woods, Dave and Peter van de Ven. "Blocked Designs for Experiments with Correlated Non-Normal Response." Technometrics. 53.2 (2011): 173-182. Electronic.

In simple linear models, the assumptions are very strict and often unattainable. Often, "many experiments measure a response that cannot be adequately described by a linear model with normally distributed errors." The authors developed a general method of creating efficient blocked designs where the response is distributed as an exponential family using Generalized Estimating Equations. "This methodology is appropriate when the blocking factor is a nuisance variable, as often occurs in industrial experiments." Using both a systematic search and a block optimal design for a Generalized Linear Model, the results are more efficient than using an optimal GLM design.  This article is useful as I am trying to clarify my statistical part of the project. This allows me to gain an idea of the type of projects Dr. Woods is involved with.