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Augmented block designs are an experimental design used in agriculture and scientific research to test both replicated and unreplicated treatments. Replicated treatments are tested in each block, while unreplicated treatments occur only once per block. This design offers advantages such as time and cost savings, flexibility, and critical comparisons. However, it comes with disadvantages like less precision for comparing unreplicated treatments and loss of information when data is missing. Applications include preliminary screening, demonstrations, testing extremes, and extra controls. Analysis involves using anova and orthogonal contrasts for controls and treatments, and adjusting unreplicated treatment means for block effects.
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Augmented Blocks
Have both replicated and unreplicated treatments Replicated treatments are tested in each block as in a RCBD Unreplicated treatments occur in only one block - so each block has a different set of unreplicated treatments
Advantages
Disadvantages
Uses
Analysis
Extra controls
Extra unreplicated treatments
Example Experiment replicated treatments tr = 3 blocks r = 4 unreplicated treatments per block tu = 2 (total of 8 unreplicated treatments)
ANOVA for replicated treatments
Source df
Total 11
Treatment 2
Block 3
Error 6
Adjustment of unreplicated treatment means for block effect
Standard error of the difference depends on whether comparisons are for replicated or unreplicated treatments Replicated treatment means are averages for all blocks Unreplicated treatments are single observations
LSD = t.05SED df = df for MSE