• Title of article

    Designing field experiments which are subject to representation bias

  • Author/Authors

    Rob Deardon، نويسنده , , Steven G. Gilmour، نويسنده , , Neil A. Butler، نويسنده , , Kath Phelps & Roy Kennedy، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2006
  • Pages
    16
  • From page
    663
  • To page
    678
  • 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 dispersalsimulation
  • Journal title
    JOURNAL OF APPLIED STATISTICS
  • Serial Year
    2006
  • Journal title
    JOURNAL OF APPLIED STATISTICS
  • Record number

    712065