Agriculture Reference
In-Depth Information
N 1
N 2
N 3
N 3
N 2
N 1
N 2
N 3
N 1
V 6
V 5
V 4
V 2
V 3
V 3
V 1
V 2
V 1
V 3
V 6
V 6
V 5
V 1
V 2
V 4
V 4
V 5
Replication I
Replication II
Replication III
Figure 6.4 Layout of a split-block design. Horizontal treatments are six different rice varieties
and vertical treatments are three different nitrogen rates (0, 60, 120 kg/ha). (From Gomez, K. A.,
and A. A. Gomez. 1984. Statistical Procedures for Agricultural Research , 2nd ed. New York: John Wiley
& Sons, p. 110.)
in a continuous strip, which is easier when using equipment. Figure 6.4
shows an example of just such a layout where the horizontal treatments
are varieties and the vertical treatments are nitrogen fertilizer rates. It
is easy to see, particularly for the fertilizer application, that treatment
application is more easily facilitated with such a design.
The degree of precision for measuring the two factors is equiva-
lent, while the degree of precision for the interaction effect is increased
(Table 6.2). Along with facilitating treatment application, such designs
would be desirable where the interaction effect is of particular interest.
Load the dataset Splitblock.dta, which is a dataset of six rice vari-
eties and three nitrogen fertilizer rates (Gomez and Gomez, 1984,
p. 110). Enter the following command:
anova yield rep var / var # rep fert / fert # rep var # fert /
rep # var # fert
This will result in the following output:
Number of obs = 54 R-squared = 1.0000
Root MSE = 0 Adj R-squared =
Source | Partial SS df MS F Prob > F
-------------+----------------------------------------------------
Model | 167005649 53 3151049.98
|
rep | 9220962.33 2 4610481.17 3.09 0.0902
var | 57100201.3 5 11420040.3 7.65 0.0034
var#rep | 14922619.2 10 1492261.92
 
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