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
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
Journal title :
JOURNAL OF APPLIED STATISTICS