农场带状试验的最佳设计--系统的还是随机的？
Optimal design for on-farm strip trials -- systematic or randomised?
摘要：
农学家和生物统计学家在农业试验中随机化的重要性是毫无疑问的。即使农学家将试验从小型试验扩展到大型农场试验，随机设计也要比系统设计占优势。然而，情况可能会发生变化，这取决于农场实验（OFE）的目标。如果OFE的目标是获得一个平滑的地图，显示一个可控输入的最佳水平，通过一个由行和列组成的网格覆盖整个领域，系统的设计应该优于随机设计的鲁棒性和可靠性。新的地理加权回归（GWR）的OFE和模拟研究，我们的结论是，对于大型OFE带状试验，随机设计和系统设计之间的差异是不显着的，如果处理的线性模型拟合或如果空间变异不考虑在内。但对于二次模型，系统设计优于随机设计。
英文摘要：
There is no doubt on the importance of randomisation in agricultural experiments by agronomists and biometricians. Even when agronomists extend the experimentation from small trials to large on-farm trials, randomised designs predominate over systematic designs. However, the situation may change depending on the objective of the on-farm experiments (OFE). If the goal of OFE is obtaining a smooth map showing the optimal level of a controllable input across a grid made by rows and columns covering the whole field, a systematic design should be preferred over a randomised design in terms of robustness and reliability. With the novel geographically weighted regression (GWR) for OFE and simulation studies, we conclude that, for large OFE strip trials, the difference between randomised designs and systematic designs are not significant if a linear model of treatments is fitted or if the spatial variation is not taken into account. But for a quadratic model, systematic designs are superior to randomised designs.
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