Agriculture Reference
In-Depth Information
5
v
ariationS
of
o
ne
f
actor
anova D
eSiGnS
Randomized Complete Block Design
In the previous chapter, ANOVA (analysis of variance) was intro-
duced with the simplest of experimental designs, the completely
randomized design, which is analyzed with the one-way ANOVA.
However, there can be more than one predictive or treatment effect
in a design. Probably the most common method of analyzing agricul-
tural experiments is the randomized complete block design (RCBD).
In this design, replications are arranged into blocks to reduce experi-
mental error that may occur because of differences in field location.
Often the terms
replication
and
blocks
are used interchangeably so that
a researcher might refer to an experiment with x treatments and y
replications with one replication occurring in each block. There are
experiments, as we will see later, that can have both replications and
blocks. Keep this in mind so you won't be confused as we look later at
more complex designs.
The command we will be using to look at these evermore complex
designs is
anova
, which has the form
anova
varname
[
term
[
/
] [
term
[
/
]...]][
if
] [
in
]
[
weight
] [,
options
]
where
term
is of the form
varname
[{
#
|
|
}
varname
[...]]
he
anova
command is followed by
varname
, which is the data-
set dependent variable. This is what is actually measured. The
term
,
of which there can be several, is the independent variable or the treat-
ment effects. Each
term
can have several variables (
varname
) and
interactions and/or subcategories. Interactions are noted with # and
subcategories with |.
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