R: Splip-Plot analysis

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

ANOVA: Splip plot analysis

### 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 1.2-8 Index]