Augmented Design was first introduced by Federer in 1956 (Federer, W.T. 1956. Augmented (or hoonuiaku) designs. Hawaiian Planters’ Record LV(2): 191-208).
In augmented designs the goal is to compare existing (control) treatments with new treatments that have an experimental constraint of "limited replication". To understand limited replication think about experiments that may only allow a single representation of the new treatment, this limitation may be many times due to the cost associated with the experiment, limited resources, or limited number of new units that can be used in the experiment. In contrast, the existing treatments are referred as checks and are generally replicated multiple times. With augmented design one can estimate the following:
a) Differences between checks and new treatments,
b) Differences among new treatments,
c) Differences among check treatments, and
d) Differences among new and check treatments combined.
Continuing with our simple agronomy example, a researcher may have a fertilizer type that is commonly used and regarded as the best on the market. The researcher will use this as a control treatment and compare it against 9 new types of fertilizers her/his company is developing for potential new commercial products. The challenge is the researcher has only limited field space and limited amounts of each fertilizer to conduct this experiment, so only one plot per new fertilizer can be planted, no replications. Therefore, the Augmented Design will be useful.
Негізгі бет Agumented Design analysis in R studio.
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