Handling Missing Data in a Block Design
An experiment uses a randomized complete block design with 5 treatments and 4 blocks. If one observation is missing, what is the most appropriate method for analyzing the data while preserving the integrity of the design?
A
Use statistical methods that can handle missing data in block designs
B
Re-randomize treatments only within the affected block
C
Discard the entire block containing the missing observation
D
Replace the missing value with the mean of other treatments in that block
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