Copula‐based robust optimal block designs

Autor: A, Rappold, W G, Müller, D C, Woods
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Applied Stochastic Models in Business and Industry
ISSN: 1526-4025
1524-1904
Popis: Blocking is often used to reduce known variability in designed experiments by collecting together homogeneous experimental units. A common modeling assumption for such experiments is that responses from units within a block are dependent. Accounting for such dependencies in both the design of the experiment and the modeling of the resulting data when the response is not normally distributed can be challenging, particularly in terms of the computation required to find an optimal design. The application of copulas and marginal modeling provides a computationally efficient approach for estimating population‐average treatment effects. Motivated by an experiment from materials testing, we develop and demonstrate designs with blocks of size two using copula models. Such designs are also important in applications ranging from microarray experiments to experiments on human eyes or limbs with naturally occurring blocks of size two. We present a methodology for design selection, make comparisons to existing approaches in the literature, and assess the robustness of the designs to modeling assumptions.
Databáze: OpenAIRE
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