Designing field experiments which are subject to representation bias

Abstract

The term ‘representation bias’ is used to describe the disparities that exist between treatment effects estimated from field experiments, and those effects that would be seen if treatments were used in the field. In this paper we are specifically concerned with representation bias caused by disease inoculum travelling between plots, or out of the experimental area altogether. The scope for such bias is maximized in the case of airborne spread diseases. This paper extends the work of Deardon et al. (2004), using simulation methods to explore the relationship between design and representation bias. In doing so, we illustrate the importance of plot size and spacing, as well as treatment-to-plot allocation. We examine a novel class of designs, incomplete column designs, to develop an understanding of the mechanisms behind representation bias. We also introduce general methods of designing field trials, which can be used to limit representation bias by carefully controlling treatment to block allocation in both incomplete column and incomplete randomized block designs. Finally, we show how the commonly used practice of sampling from the centres of plots, rather than entire plots, can also help to control representation bias.

Keywords:

• Experimental design
• inter-plot interference
• plant pathology
• plant disease dispersal simulation

Acknowledgements

This work was funded by the Engineering and Physical Sciences Research Council and HRI Warwick. The authors would also like to thank Mike Shaw of the University of Reading and biologists at HRI Warwick for their invaluable insights into plant pathological processes and advice in the development of the simulation program.