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Title: | Designs with complex blocking structures and network effects for agricultural field experiments |
Authors: | Koutra, V Gilmour, SG Parker, BM Mead, A |
Keywords: | design of experiments;connected experimental units;neighbour effects;nested row-column designs;treatment interference |
Issue Date: | 24-Aug-2021 |
Publisher: | Cornell University |
Citation: | Koutra, V., Gilmour, S.G., Parker, B.M. and Mead, A. (2021) 'Designs with complex blocking structures and network effects for agricultural field experiments', arXiv:2012.13425v2 [stat.ME], pp. 1-23. doi: 10.48550/arXiv.2012.13425. |
Abstract: | Copyright 2021 The Author(s). We propose a novel model-based approach for constructing optimal designs with complex blocking structures and network effects, for application in agricultural field experiments. The potential interference among treatments applied to different plots is described via a network structure, defined via the adjacency matrix. We consider a field trial run at Rothamsted Research and provide a comparison of optimal designs under various different models, including the commonly used designs in such situations. It is shown that when there is interference between treatments on neighbouring plots, due to the spatial arrangement of the plots, designs incorporating network effects are at least as, and often more efficient than, randomised row-column designs. The advantage of network designs is that we can construct the neighbour structure even for an irregular layout by means of a graph to address the particular characteristics of the experiment. The need for such designs arises when it is required to account for treatment-induced patterns of heterogeneity. Ignoring the network structure can lead to imprecise estimates of the treatment parameters and invalid conclusions. |
URI: | https://bura.brunel.ac.uk/handle/2438/24461 |
DOI: | https://doi.org/10.48550/arXiv.2012.13425 |
Other Identifiers: | arXiv:2012.13425v2 |
Appears in Collections: | Dept of Mathematics Research Papers |
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