sp.plot {agricolae}R Documentation

Splip-Plot analysis

Description

The variance analysis of a split plot design is divided into two parts: the plot-factor analysis and the sub-plot factor analysis.

Usage

sp.plot(block, pplot, splot, Y)

Arguments

block

replications

pplot

main-plot Factor

splot

sub-plot Factor

Y

Variable, response

Details

The split-plot design is specifically suited for a two-factor experiment on of the factors is assigned to main plot (main-plot factor), the second factor, called the subplot factor, is assigned into subplots.

Value

block

vector, numeric or character

pplot

vector, numeric or character

splot

vector, numeric or character

Y

vector, numeric

Author(s)

Felipe de Mendiburu

References

Statistical procedures for agricultural research. Kwanchai A. Gomez, Arturo A. Gomez. Second Edition. 1984.

See Also

ssp.plot, strip.plot, design.split, design.strip

Examples

library(agricolae)
data(plots)
model<-with(plots,sp.plot(block,A,B,yield))
# with aov
plots[,1]<-as.factor(plots[,1])
AOV <- aov(yield ~ block + A*B + Error(block/A),data=plots)
summary(AOV)
[Package agricolae version 1.2-6 Index]