sp.plot: Splip-Plot analysis
In myaseen208/agricolae: Statistical Procedures for Agricultural Research

sp.plot

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

ANOVA: Splip plot analysis

Author(s)

Felipe de Mendiburu

References

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

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)

myaseen208/agricolae documentation built on April 4, 2023, 5:23 a.m.