Randomized Complete Block Design
The design allows the grouping of experimental subjects of heterogeneous characteristics into more or less homogenous groups called blocks. By grouping them based on some identified characteristics, the difference that would be observed will be largely due to treatment and not due to their characteristics.
Another Description of RCBD:
Probably the most used and useful of the experimental designs. Takes advantage of grouping similar experimental units into blocks or replicates. The blocks of experimental units should be as uniform as possible. The purpose of grouping experimental units is to have the units in a block as uniform as possible so that the observed differences between treatment will be largely due to “true” differences between treatments.
Each replicate is randomized separately.
Each treatment has the same probability of being assigned to a given experimental unit within a replicates. Each treatment must appear at least once per replicate.
This is a two-step Completely Randomized Design, as it involved: 1. Grouping of experimental subjects into blocks, and
2. Application of complete randomization.
Advantages of RCBD:
Generally more precise than the CRD
No restriction on the number of treatments or replicates.
Some treatments may be replicated more times than others.
Missing plots are easily estimated.
Whole treatments or entire replicates may be deleted from the analysis. If the experimental error is heterogeneous, valid comparisons can still be made.
Disadvantages of the RCBD:
Error df is smaller than that for the CRD (problem with a small number of treatments) If there is a large variation between experimental units within a block, a large error term may result (this may be due to too many treatments) If there are missing data, a RCBD experiment may be less efficient than a CRD.
Appropriateness of the RCBD:
If the experiment subjects can be grouped or...
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