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Optimal design of experiments on connected units with application to social networks

Research output: Contribution to journalArticle

Ben M. Parker, Steven G. Gilmour, John Alexander Schormans

Original languageEnglish
Pages (from-to)455-480
JournalAPPLIED STATISTICS
Volume66
Issue number3
Early online date25 Aug 2016
DOIs
Publication statusPublished - Apr 2017

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Abstract

When experiments are performed on social networks, it is difficult to justify the usual assumption of treatment-unit additivity, due to the connections between actors in the network. We investigate how connections between experimental units affect the design of experiments on those experimental units. Specifically, where we have unstructured treatments, whose effects propagate according to a linear network effects model which we introduce, we show that optimal designs are no longer necessarily balanced; we further demonstrate how experiments which do not take a network effect into account can lead to much higher variance than necessary and/or a large bias. We show the use of this methodology in a very wide range of experiments in agricultural trials, and crossover trials, as well as experiments on connected individuals in a social network.

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